Security Analytics: Risk Analysis for an Organisation's ... · Security Analytics: Risk Analysis for an Organisation's Incident Management Process Marco Casassa Mont, Richard Brown,

Security Analytics: Risk Analysis for an Organisation's Incident Management

Process Marco Casassa Mont, Richard Brown, Simon Arnell, Neil Passingham

HP Laboratories

HPL-2012-206

Keyword(s): Security Analytics; Risk Analysis; What-if Analysis; Incident Management Processes; SOC

Abstract: This document is an example of the type of report an organisation would receive at the end of a HP Security

Analytics engagement. The focus is on the analysis of the security risks and performance of the organisation's

Security Incident Management Processes and related Security Operation Centre (SOC)'s activities. HP Labs carried

out the underlying R&D work in collaboration with HP Enterprise Security Services (HP ESS) and involved

analysis of processes, probabilistic modeling, simulation and "what-if" analysis for some of HP's key customers. The

outcome of this was a set of case studies from which we have been able to create this more general anonymised

report illustrating the richness of the risk assessment and "what-if" analysis that has been carried out. The lifecycle

management of security is critical for organisations to protect their key assets, ensure a correct security posture and

deal with emerging risks and threats. It involves various steps, usually carried out on an ongoing, regular basis,

including: risk assessment; policy definition; deployment of controls within the IT infrastructure; monitoring and

governance. In this context, Security Information & Events Management (SIEM) solutions play a key role. Even the

best information security practices and investments in security controls cannot guarantee that intrusions – accidental

and criminal activities – and/or other malicious acts will not happen. Controls can fail, be bypassed or become

inadequate over time; new threats emerge. Managing such incidents requires detective and corrective controls to

minimise adverse impacts, gather evidence, and learn from previous situations in order to improve over time. These

incident management processes are usually run in the context of a SOC and/or as part of specialised Computer

Security Incident Response Teams (CSIRTS), built on top of SOCs. Even with SIEM solutions in place, a potential

major risk for the organisation arises due to delays introduced in assessing and handling known incidents: this may

postpone the successful resolution of critical security incidents (e.g. devices exposed on the Internet, exploitation of

privileged accounts, deployed malware, etc.) and allow for further exploitation. Another related risk can be

introduced by sudden and/or progressive changes of the threat landscape, due to changing economic and social

scenarios, new business activities or process failings within the existing IT services. This might create unexpected

volumes of new events and alerts to be processed by the security team and as such, introduce additional delays.

Hence, it is important for an organisation to understand the risk exposure due to their Incident Management

processes, explore potential future scenarios (e.g. changes in available resources or threats landscapes or adoption of

Cloud solutions) and identify suitable ways to address related issues, e.g. by introducing process changes and/or

making investments in security controls.

External Posting Date: September 6, 2012 [Fulltext] Approved for External Publication

Internal Posting Date: September 6, 2012 [Fulltext]

Copyright 2012 Hewlett-Packard Development Company, L.P.

Security Analytics: Risk Analysis for an Organisation’s Incident

Management Processes

(1) Marco Casassa Mont, (1) Richard Brown, (2) Simon Arnell, (2) Neil Passingham

(1) Cloud & Security Lab, HP Labs, Bristol, UK (2) HP Enterprise Security Services

marco.casassa‐[email protected], [email protected], [email protected], [email protected]

Abstract

This document is an example of the type of report an organisation would receive at the end of a HP Security

Analytics engagement. The focus is on the analysis of the security risks and performance of the organisation’s

Security Incident Management Processes and related Security Operation Centre (SOC)’s activities. HP Labs carried

out the underlying R&D work in collaboration with HP Enterprise Security Services (HP ESS) and involved analysis of

processes, probabilistic modeling, simulation and “what‐if” analysis for some of HP’s key customers. The outcome

of this was a set of case studies from which we have been able to create this more general anonymised report

illustrating the richness of the risk assessment and “what‐if” analysis that has been carried out.

The lifecycle management of security is critical for organisations to protect their key assets, ensure a correct

security posture and deal with emerging risks and threats. It involves various steps, usually carried out on an

ongoing, regular basis, including: risk assessment; policy definition; deployment of controls within the IT

infrastructure; monitoring and governance. In this context, Security Information & Events Management (SIEM)

solutions play a key role. Even the best information security practices and investments in security controls cannot

guarantee that intrusions – accidental and criminal activities – and/or other malicious acts will not happen.

Controls can fail, be bypassed or become inadequate over time; new threats emerge. Managing such incidents

requires detective and corrective controls to minimise adverse impacts, gather evidence, and learn from previous

situations in order to improve over time. These incident management processes are usually run in the context of a

SOC and/or as part of specialised Computer Security Incident Response Teams (CSIRTS), built on top of SOCs.

Even with SIEM solutions in place, a potential major risk for the organisation arises due to delays introduced in

assessing and handling known incidents: this may postpone the successful resolution of critical security incidents

(e.g. devices exposed on the Internet, exploitation of privileged accounts, deployed malware, etc.) and allow for

further exploitation. Another related risk can be introduced by sudden and/or progressive changes of the threat

landscape, due to changing economic and social scenarios, new business activities or process failings within the

existing IT services. This might create unexpected volumes of new events and alerts to be processed by the

security team and as such, introduce additional delays. Hence, it is important for an organisation to understand the

risk exposure due to their Incident Management processes, explore potential future scenarios (e.g. changes in

available resources or threats landscapes or adoption of Cloud solutions) and identify suitable ways to address

related issues, e.g. by introducing process changes and/or making investments in security controls.

HP Security Analytics is uniquely positioned to provide the analysis of the involved risks, explore what‐if scenarios

and provide decision support for decision makers. This type of Security Analytics assessments is now available as a

service, provided by HP ESS.

Security Analytics ReportRisk Analysis: Security Event & Incident

Management ProcessesFor Illustrative Purposes Only

HP Security Analytics Final Report

Page 1 of 80

Disclaimer

This document is an example of the type of report a customer would receive at the end of a Security

Analytics engagement [10]. The focus is on the analysis of the security risks and performance of the

customer’s Security Events & Incident Management Processes.

The report is loosely based around a real customer case study, but all contextual information, event

and incident management processes, empirical data, analyses and conclusions have been modified in

order to protect this customer’s identity and confidential information. As a result we believe this

report reflects well the current situation many large organizations find themselves in with respect to

the management of security events and related incidents.

For this purpose, we introduce a fictitious company, ServiceBizWorld.

This report focuses on two key processes in the incident management and remediation space - the

process of analyzing and handling security events/alerts (to the point these events are either closed or

classified as false positives or turned into incidents) and the process of managing and remediating to

security incidents - which have been generalized (and represented with templates) and should be of

relevance to many customers. The report shows how Security Analytics can be applied in carrying out

risk assessment and what-if analyses.

The analysis discussed in this report can be applied also to those companies that currently do not have

explicit event and incident management processes in place but are planning to create them. In this

context, Security Analytics can be of help to explore the impact of making different process choices

(in terms of security risk and productivity) along with the implications of making specific

technological investments.

Security Analytics [10] has also been successfully applied to the areas of Identity and Access

Management, Vulnerability and Threat Management and Web Infection.


Page 2 of 80


Page 3 of 80

Security Analytics Risk Analysis: Security Event & Incident Management Processes

Executive Summary

HP Labs conducted a detailed analysis of the current ServiceBizWorld’s Security Events and Incident

Management Processes. It was undertaken using HP’s Security Analytics modelling methodology.

The analysis focused on the Event/Alert Processing & Remediation Process and the Incident Management

Process. The latter is triggered when Major (IT) Security Incidents are identified by the SOC team. The analysis

included the examination of the risk exposure arising from current practice and process steps measured as the

time to identify and remediate security incidents. Models have been developed to simulate the arrival of

events/alerts and the execution of the involved processing steps. These models took into account the complexity

of events/alerts and their rate, the interactions with Third Parties (TPs), TP behaviours and non compliance

issues, various SOC team’s management steps. They measured, among other things, the time required to:

process events/alerts; identify minor and major security incidents and remediate them; identify false positives.

A first outcome of the analysis highlighted the complexity of the current processes; the models provide an

explicit representation of the involved steps.

Experimental results confirmed that interactions with TPs constitute a major bottleneck. Specifically they

account for 60-70% of the time required to process events/alerts (i.e. between 15-50 days). This is a critical

issue, as it negatively affects the processing of Major Security Incidents. Two key aspects have been identified

as root causes: the lack of specific SLAs with TPs about how information should be provided to the SOC Team;

the lack of information availability for TPs.

In this context, three what-if scenarios were explored using the model of the Event/Alert Processing &

Remediation Process (the most critical of the two analysed processes) to assess the impact on risk exposure and

performance, in case of: (1) improving SLAs with TPs; (2) changing threat environments; (3) improving

information availability for TPs. The main findings show that:

The definition of SLAs for TPs (e.g. about response time and number of iterations with the SOC Team) can

dramatically improve the overall performance and reduce the risk exposure by at least an order of

magnitude;

The current process might expose ServiceBizWorld to additional risks - in terms of delays to identify

security incidents and saturation of TP resources/personnel - if the daily number of new events to be

processed increases by about 30%;

Investments in new controls not only can improve the overall TP information availability and performance

(estimated to be an order of magnitude) but also help to cope with worsening threat landscapes.

Specifically, the adoption of information request templates and manual scripts can ensure process resilience

to a 60% increase of the daily number of new events/alerts to be processed. The introduction of automation

of scripts and/or workflows enables process resilience to an increase of 90% of events/alerts.

A what-if scenario for the Incident Management Process showed similar outcomes and improvements when

templates and automation are introduced to deal with incident response & remediation tasks.

These findings depend on the assumptions made and the information available at the time of the analysis. They

provide a starting point for conversations between ServiceBizWorld, TPs and the SOC Team, on expectations,

policy & SLA changes, as well as on potential new investments, to improve the current process performances,

reduce risk exposure and deal with contingency planning for worsening threat environments.


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Content

Executive Summary 3

Content 4

1 Glossary 6

2 Overview of the Report 7

3 Area Selected for Investigation: Goals and Scope 8

4 Overview of Security Event & Incident Management Processes 10

5 Analysis of ServiceBizWorld Security Event & Incident Management Processes 13

6 Security Analytics Approach 15

7 Models 17

7.1 Model 1: Security Event/Alert Processing and Remediation 17

7.1.1 Modelled Process Areas 19

7.1.1.1 Events and Alerts 19

7.1.1.2 Initial Assessment Phase 19

7.1.1.3 SOC Team Interactions with TPs 20

7.1.1.4 SOC Team Final Assessment 21

7.1.1.5 Event Closure 22

7.1.1.6 Security Incident 23

7.1.1.7 TP Non Compliance 23

7.1.1.8 Handling False Positives and Known Problems 24

7.1.2 Metrics 25

7.1.3 What-if Scenarios 26

7.1.3.1 Impact of Changing SLAs for TPs 26

7.1.3.2 Impact of Changes of the Threat Environment 28

7.1.3.3 Impact of Investments to Improve Information Availability for TPs 32

7.2 Model 2: Incident Management Processes 36

7.2.1 Modelled Process Areas 38

7.2.1.1 Events 38

7.2.1.2 Initial Assessment Phase 38

7.2.1.3 Information Gathering from Risk Management Team 38

7.2.1.4 TP Handling of Incident Response 39

7.2.1.5 TP Incident Remediation 40

7.2.1.6 Risk Management 40

7.2.2 Metrics 40

7.2.3 What-If Scenarios 41

7.2.3.1 Impact of Investments to Improve the Process Performance 41

8 Results Regarding Current State 44

8.1 Model 1: Events/Alerts Processing and Resolution 44


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8.1.1 Summary 48

8.2 Model 2: Incident Management Process 49

8.2.1 Summary 50

9 Results for What-If Scenarios 52

9.1 Model 1: Security Event/Alert Processing and Resolution 52

9.1.1 Impact of Changing SLAs for TPs 52

9.1.1.1 Summary 57

9.1.2 Impact of Changes of the Threat Environment 58

9.1.2.1 Summary 62

9.1.3 Impact of Investments to Improve Information Availability for TPs 63

9.1.3.1 Summary 71

9.2 Model 2: Incident Management Process 72

9.2.1 Impact of Investments to Improve the Process Performance 72

9.2.1.1 Summary 75

10 Conclusion 76

11 References 77

A.1 List of parameters - Model 1: Events/Alerts Processing and Resolution 78

A.2 List of parameters - Model 2: Incident Management Process 80


Page 6 of 80

1 Glossary

CSIRTS Computer Security Incident Response Teams

ITIL Information Technology Infrastructure Library

Major Security Incident

Serious Security Incident with potential Major Security & Business Impacts

SA Security Analytics

SIEM Security Information and Event Management

SIM/SEM Security Information Management/Security Event Management

SLA Service Level Agreement

SOC Security Operations Centre

TP Third Party


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2 Overview of the Report

This final report presents the findings of the security risk analysis for the ServiceBizWorld’s Event &

Incident Management Processes, based on the Security Analytics methodology [10] developed by HP

Labs.

Section 3 describes the problem space, the scope and the goals of this risk analysis.

Section 4 provides a general overview of the Security Event and Incident Management area.

Section 5 specifically analyses the current security event and incident management processes in place

at ServiceBizWorld.

Section 6 provides an overview of the HP Security Analytics approach and how it has been applied to

this area, to explore the problems investigated in this report.

Section 7 describes the two Security Analytics models developed by HP Labs, in collaboration with

ServiceBizWorld, related to: (1) their Events/Alerts Processing & Remediation Process; (2) their

Incident Management Process. This section also describes the agreed metrics and the what-if

scenarios that have been investigated.

Section 8 provides a detailed discussion of the risk assessment results obtained from the current

Security Analytics models.

Section 9 presents and discusses the outcomes of the analysis of various, related what-if scenarios.

Section 10 draws the final conclusions.


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3 Area Selected for Investigation: Goals and Scope

The focus of the HP Labs security risk analysis is on the event & incident management processes that

are currently deployed and run by ServiceBizWorld. These processes are critical for the organisation

to identify potential security issues, analyse and mitigate them. They are complex and involve various

stakeholders: the SOC Centre/Security Team; the Risk Management Team; various Third Parties

(TPs). Specifically, these TPs include ServiceBizWorld’s IT department, ServiceBizWorld’s business

groups and the IT departments of external companies, which provide (business and IT) services to

ServiceBizWorld in the Cloud and/or in outsourcing.

The issues arising in this area, explored with the HP Security Analytics methodology, are captured in

the following statements:

– How to ensure that the right incident management processes are in place to handle both

current security threats and potential future critical ones?

– What is the risk exposure for ServiceBizWorld? What is the impact of changing threat

environments?

The area of Security Incident Management is wide as it covers various types of incidents, including

the ones related to: IT infrastructure; people behaviours; system failures; fraud; etc.

The security risk analysis discussed in this report focuses on IT security events and incidents. The

following priorities have been identified by ServiceBizWorld:

the need to be confident that ServiceBizWorld is ready to handle current and future security

threats;

the need to be able to justify investments and process changes.

The goals for the security risk analysis are:

Analyse the risk exposure of ServiceBizWorld due to the current security incident

management processes;

Analyse the impact of introducing new SLAs for the involved stakeholders and/or deploying

new controls within the incident management processes;

Analyse the impact on current processes (in terms of risk exposure) of changes of the threat

landscape (e.g. increase of number of new events/alerts to be processed);

Analyse the impact of deploying new controls within the current processes to mitigate

changes of the threat landscape.

A secondary goal of this analysis is to identify potential productivity issues related to current Incident

Management Processes and explore suitable ways for improvement.

The security analytics methodology adopted for this investigation has been specifically designed to

answer these types of questions. The methodology is based on system environment modelling and

predictive simulations, which allow the experimental exploration of risk and productivity across the

set of outcomes for the current incident management and remediation processes. It also provides the

ability to examine the impact of deploying different types of controls and/or process changes along

with exploring the impact of a changing threat landscape.

Changes to the event & incident management processes need to have the support of the various

involved stakeholders and potentially continued investments in a platform that can facilitate the


Page 9 of 80

overall processes. This requires strategic alignment with ServiceBizWorld’s overall business

objectives and risk posture.

The final aim of the analysis discussed in this report is to provide evidence to ServiceBizWorld and its

Security & Risk Management teams to support their decision making process, specifically in

identifying suitable policies and SLAs changes and/or justify future investments in process changes

and controls.


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4 Overview of Security Event & Incident Management Processes

The lifecycle management of security is critical for organisations, to protect their key assets, ensure a

correct security posture and deal with emerging risks and threats. It involves various steps, usually

carried out on an ongoing, cyclic basis, including: risk assessment; policy definition; deployment of

controls within the IT infrastructure; monitoring and governance.

In this context, Security Event Monitoring and Incident Management play a key role. Even the best

information security practice and security control investments cannot guarantee that intrusions,

accidental and criminal activities and/or other malicious acts will not happen. Controls can fail, be

bypassed or become inadequate over time. New threats could emerge.

ITIL [1] defines an incident as "any event which is not part of the standard operation of a service and

which causes, or may cause, an interruption to, or a reduction in, the quality of service". A similar

definition could apply in the context of security incidents, which might not only cause a reduction in

the quality of service but also expose the organisation to additional risks.

This document specifically focuses on IT security incidents and the processes that organisations put in

place for their management and remediation.

Various types of security incidents are of concerns to organisations, including: deployment of

malicious software and malware within critical IT systems; misuse of systems and services by users;

unauthorised access to resources; computer sabotage and damages; intrusion of critical

systems/services; information theft and espionage.

Managing incidents involves detective and corrective controls to minimise adverse impacts, gather

evidence, learn from previous situations and improve over time. When security incidents occur, it is

important for an organization to effectively manage and respond to them. The speed with which an

organization can recognize, analyze, and respond to a security incident will limit the impact of the

damage and potentially lower the cost of recovery [2]. This process carried out by organisations to

collect, identify, analyze, and determine an organizational response to security incidents is called

incident management. Processes are usually put in place to deal with incident management. The staff,

resources, and infrastructure used to perform this function makeup the incident management

capability.

Various controls are currently available for organisations, including Security Information and Event

Management (SIEM) solutions and Security Operations Centres (SOCs) [5].

SIEM solutions, including HP ArcSight [3], RSA enVision [4], etc. provide real-time analysis of IT

and security events generated from the IT infrastructure including network hardware, systems,

applications and services. Various degrees of correlations and analysis are offered by these solutions

to focus on the root causes of events, identify potential critical alerts, store logs for forensic purposes

and generate reports for compliance management.

However, the events and alerts generated by these systems often require analysis and further

processing by security specialists to fully understand their nature and implications, identify critical

incidents and apply the right strategy to mitigate them.

In this context, Security Event & Incident Management Processes need to be put in place, along with

security teams, to execute on the management of events and alerts and the resolution of related

incidents.

Figure 4-1 shows the key steps that are usually involved in these processes:


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Figure 4-1. Security Event & Incident Management Processes

They include:

Collection of events and alerts: the initial phase, where filtered/correlated events and alerts

are provided by SIEM solutions to the security team;

Triage and initial analysis: it involves an initial analysis and assessment of the events and

alerts, to identify potential known problems and false positives. The output of this step is

either a decision to close the event/alert (in case of known issue or false positive) or to

proceed with a deeper analysis;

Collection of additional information from the involved stakeholders: it usually involves the

collection of additional information about events/alerts, potentially from the involved

stakeholders, i.e. the IT department, business areas, etc. This information is necessary to

gather further evidence and data to assess the seriousness of the event/alert, identify the root

causes, assess the involved risks and support informed decision making;

Final Assessment: it involves making a final decision about the nature of the events and alerts.

The collected evidence might still indicate that it is a false positive or it should be closed as

not critical for the organisations. Alternatively, a security incident might be raised and/or

escalated for remediation;

Identification of Remediation steps for the Incident: it involves the identification of

remediation steps to deal with the incident. This activity is usually carried out jointly with the

involved parties within the organisation;

Incident Remediation: it involves the actual resolution and remediation of the security

incident by the involved entity, along with handling any residual risks due to failures to

mitigate the security incident.


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It is important to notice that the management of false positives and known problems usually consume

“resources” that could be used for the investigation of real security incidents. Ideally, it is desirable to

minimise the number of false positives. This usually requires fine tuning activities between the SIEM

solutions (raising events/alerts) and the initial assessment phase.

The incident management processes are usually run in the context of Security Operation Centres

(SOC) [5] and/or as part of specialised Computer Security Incident Response Teams (CSIRTS) [6],

built on top of SOC centres.

The work of the involved security team(s) can be supported by a variety of technical controls and

solutions including workflow systems, incident tracking and support solutions, knowledge bases and

collaborative tools, etc. However, quite often the involved processes are driven by human activities

and the investigative skills of the security team members. As such, these processes might be subject to

a variety of issues and potential failures, including:

Delays due to lack of resources (personnel) to handle large volumes of events/alerts;

Delays due to complex process steps and failures in human interactions and communications;

Bottlenecks generated by some of the stakeholders to retrieve relevant information, e.g. by IT

departments or business groups;

Failures in assessing the severity of events/alerts and their correct categorization as

incidents;

Lack of tools, expertise and capabilities to remediate security incidents.

These issues and failures can expose the organisation to additional risks.

A potential major risk for the organisation is due to delays introduced in assessing and handling

known incidents: this might postpone the successful resolution of critical security incidents (e.g.

devices exposed on the Internet, exploitation of privileged accounts, deployed malware, etc.) and

allow for further exploitation.

Another related risk can be introduced by sudden or progressive changes of the threat landscape, due

to changing economical and social scenarios and/or new business activities. This might create

unexpected volumes of new events and alerts to be processed by the security team and as such,

introduce additional delays.

To summarise, the space of Security Event & Incident Management is complicated and with many

uncertainty points: it is subject to changing threat environments; it is defined by a variety of processes

and process steps relying on people, human interactions, controls and information flows; it is subject

to technical issues and failures.

It is important for an organisation to understand their risk exposure due to the Incident Management

processes and identify suitable ways to address related issues, e.g. by introducing process changes

and/or making investments in security controls.

HP Security Analytics is uniquely positioned to provide the analysis of the involved risks, explore

what-if scenarios and provide decision support for decision makers.

This report discusses the findings of the risk analysis carried out by HP Labs for ServiceBizWorld

event & incident management processes, along with the exploration of what-if scenarios aiming at

providing specific decision support and enabling further discussions between the involved

stakeholders.


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5 Analysis of ServiceBizWorld Security Event & Incident

Management Processes

The Security Operations Centre (SOC) team currently runs the core ServiceBizWorld processes for

(IT) security event & incident management processes.

ServiceBizWorld has a complex IT and business infrastructure. Part of its IT and service

infrastructure is run by third parties, either in the context of outsourcing contracts and/or by using

services in the Cloud.

In order to assess the specific security event & incident management processes, identify potential risk

exposures for ServiceBizWorld and explore relevant what-if scenarios, HP Labs requested

information from key SOC and ServiceBizWorld personnel. Information and data have been provided

to support this analysis along with detailed explanations of the various process steps and interactions.

Various stakeholders are involved in these processes:

The SOC team: it provides the key coordination, supervision and assessment capabilities for

the management of events/alerts and the processing of related incidents;

The Security Risk Management team: it is the ServiceBizWorld team that provides further

guidance on priorities and decisions about incident management. It has a longer term,

strategic view on security aspects and related policies driven not only by security

requirements but also by business needs;

Various third parties, including ServiceBizWorld’s IT department, ServiceBizWorld’s

business groups and the IT departments of external companies, which provide (business and

IT) services to ServiceBizWorld in the Cloud and/or in outsourcing.

The relevant SOC Event & Security Incident Management activities can be classified in two types of

processes, shown in Figure 5-1:

Events/Alerts Processing and Resolution Process

Security Incident Management Process

Events/Alerts

- Known Problems- False Positives- Event Closure- Minor Security

Incidents

Major Security Incidents

- Remediated Security Incidents- Risk Management

Figure 5-1. ServiceBizWorld’s Security Event & Incident Management Processes


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The first process, referred in this report as “Events/Alerts Processing and Resolution Process”,

primarily aims at: providing the initial assessment of events/alerts; gathering of relevant information

from the involved TPs to further analyse the events/alerts; dealing with the final assessment of

events/alerts and their classification as false positives, known problems, events to be closed, minor

security incidents and major security incidents.

This process is fed by a variety of events/alerts, originated by notifications sent to the SOC team by

various SIEM tools and TPs. The SIEM tools include, among others, the HP ArcSight [3] and RSA

enVision solutions [4].

Specifically, the events/alerts collected from the SIEM system could relate to:

Managed internal firewalls;

Managed network devices;

Domain authentication events;

Malware security events;

Authentication events.

Based on information provided by the SOC team, on average 35-40 events/alerts are processed on

daily basis, i.e. about 12000-15000 per year.

Among all these events/alerts, a small part of them involve Major Security Incidents. These are

critical security incidents for which a full report has to be provided to the Risk Management team and

that trigger the second process. These are also referred to as “Managed Security Incident” as the SOC

team is directly involved in the incident resolution process. On average, 800-900 major security

incidents are raised on yearly basis.

The category of Major (IT) Security Incidents include: discovery of exposure of ServiceWorldBiz’s

devices and systems to the Internet; unauthorised privilege escalation; malware security incidents;

security log cleaning; misuse of authentication tokens; incidents raised from internal firewalls.

The second process, referred in this report as “Security Incident Management Process” is triggered

when Major Security Incidents are raised by the SOC team.

This process involves the steps of: identifying and agreeing remediation requirements for major

security incidents, related to TPs (task usually carried out jointly by the SOC team and the Risk

Management team); the actual phase involving TPs remediation to the incident.

Next sections provide further detail of how the information about these two processes has been

interpreted and captured in Security Analytics models to carry out the investigations described in

Section 3.

These models will primarily focus on the interactions between the SOC team and Third Parties (TPs).

The key interactions with the Risk Management team have also been modelled.


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6 Security Analytics Approach

Two Security Analytics models have been built, one for each process mentioned in Section 5, in order

to carry out the analysis of ServiceBizWorld’s risk exposure to the Security Event & Incident

Management Processes:

1. Model #1: Events/Alerts Processing and Resolution Process;

2. Model #2: Security Incident Management Process.

Each model represents the involved process steps, interactions with TPs, information flows and

decision points.

These models measure the time to carry out various activities and determine the potential process

outcomes: false positives, known problems, events to be closed, minor security incidents and major

security incidents. Additional metrics have been used to count the occurrence of such outcomes.

These metrics, discussed in detail in Section 7, have been used to provide the required estimates of

risk exposure and productivity.

We anticipate that the interactions with TPs introduce a major bottleneck with a negative impact on

risk exposure and productivity. As such, the related parts of the processes have been subject of

specific analysis and risk assessment (as well as what-if analysis), as discussed in the next Sections.

The Security Analytics models have been used to carry out the investigations presented in Section 3,

i.e. to identify:

The level of risk exposure for ServiceBizWorld, to manage and mitigate IT security incidents

with current processes, based on the overall time required to handle these incidents;

The impact of bottlenecks introduced by TPs, in the current processes;

The predicted improvements of changing SLAs with TPs and/or introducing new controls within

current processes (what-if scenario);

The level of risk exposure to manage and mitigate IT security incidents, in case of changing threat

landscapes, based on the overall time required to handle these incidents (what-if scenario);

The predicted improvements, in case of a changing threat landscape, by introducing new controls

within current processes (what-if scenarios).

Specifically, the two models have been built by using a flow chart-based graphical representation.

To validate them, they have initially been used to provide an estimate of the risk exposure to and

productivity for current processes. This phase was iterated over a few times with the SOC and Risk

Management teams to ensure that the right process steps and the correct empirical data were captured

by the. After their validation, the two models have been used to explore “what-if scenarios”, as

requested by ServiceBizWorld.

The visual representations of the models were created by using the HP proprietary Gnosis modelling

toolset, with the various shapes in the model instantiated with a set of parameters. The models were

then transformed by the toolset into executable code, which was used to run Monte Carlo simulations.

This whole analytic chain is shown in Figure 6-1.


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Figure 6-1. Visual Representation of the Model/Experiment/Results Chain

The two models were drawn by using visual diagrams (shown in the next sections) together with

detailed descriptions of the involved parameters. The complete list of parameters can be found in

Appendices A.1 and A.2. The visual diagrams should be interpreted as follows:

The star-shaped components represent the events that occur at regular intervals as defined

with a probability distribution in a model (e.g. 7 events/alerts received per day), each star-

shaped component starts a separate flow that runs in parallel to other flows, within

simulations;

The rectangular shapes correspond to the process steps each with an internal logic, that

consists of time duration (e.g. a step takes 1 day to complete) or some manipulations of

internal parameters (e.g. number of iterations with TPs);

The rhombus shapes are if-type decision boxes, that return Boolean values i.e. true or false

based on Bernoulli trial for a certain probability (e.g. the probability that an event/alert is a

false positive has a probability of 0.1);

The people-shaped icons represent resources that are used by different process steps (e.g.

members/people of the TP security staff);

The cylinder shape stores the values of certain parameters that, for example, represent the

current state (e.g. the number of iterations with TPs, the number of incidents, false positives,

etc.);

Finally, the process dynamics of the model is captured by the arrows connecting events to

processes steps and decision boxes.


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7 Models

This section presents the two models built by HP Labs to carry out the risk and performance analysis

for the ServiceBizWorld’s Event & Incident Management processes. It also describes the set of

metrics used to convey analytic results and the what-if scenarios that have been explored with the

models.

7.1 Model 1: Security Event/Alert Processing and Remediation

The first model, related to the SOC Security Event/Alert Processing & Remediation Process is shown

in Figure 7-1.

The model captures the current process steps, specifically:

1. Set of Events/Alerts that are analysed and managed within the process;

2. Various event/alert processing phases, including: Initial Assessment Phase, SOC team’s

Interactions with TPs, SOC team’s final assessments;

3. Various possible outcomes of the execution of the process: event/alert closure, raising

security incident, TP non compliance; handling false positives and known problems.

The various process steps are annotated with the empirical data gathered from the SOC and Risk

Management teams. They reflect the current situation in terms of frequency of events, duration of

process steps and likelihood of making certain decision. The complete list of the empirical data used

in this model is available in Appendix A.1.

When executed, this model simulates the arrival of events and alerts and the various processing steps

in order to determine the outcomes i.e. if an event/alert has to be closed, if it is a false positive/known

problem or if it has to be escalated as a minor or major security incident. The model has been

instrumented with various metrics, discussed in this section, to measure the impact in terms of risk

exposure and performance.

The next sections described in detail each of the key parts highlighted in the model.


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Figure 7-1. Model 1: SOC Security Event/Alert Processing and Remediation


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7.1.1 Modelled Process Areas

7.1.1.1 Events and Alerts

Figure 7-2 shows the set of events and alerts that are managed within this process:

Figure 7-2. Model 1: Events and Alerts

Specifically there are 2 types of events/alerts that are processed:

SOC Events and Alerts received from SOC SIEM tools: these are the SOC events and alerts

received from SIEM tools such as HP ArchSight and RSA enVision. On average, 20 of these

events/alerts are generated on daily basis;

Notification of IT Security Events/Alerts from TPs: these are specific notifications of IT

security events/alerts from third parties. On average, 15 of these events/alerts are generated on

daily basis.

7.1.1.2 Initial Assessment Phase

Figure 7-3 illustrates the various process steps that are carried out by the SOC team to initially assess

the new event/alert:

Figure 7-3. Model 1: Initial Assessment Phase

This includes the following steps:

An initial assessment of the event/alert, usually taking between 1 hour and 2 hours;

A decision if the event/alert is a known security problem and in case it is, if the threat level

has been changed. The available empirical data suggests that 10% of cases are known issues.

In 5% of them the threat level has changed. In case it is a known problem, it is handled as

such;

In case it is not a known problem or the threat level changed, a decision is made if there is any

need to notify the Risk Management team. This usually happens in 15% of cases. In this case,

the SOC team has to prepare a briefing for the Risk Management team and agree on the


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relevant remediation. This usually takes between 5 hours and 1 day. An additional decision is

made if this event/alert is actually an incident and its category has been established. This

happens in 80% of cases. The empirical data suggests that in 10% of cases the security

incident is raised as a Major Security Incident;

If there is no need to brief the Risk Management team and/or the incident category has not

been established, then the process continues with the analysis of the event/alert. This might

require gathering information from TPs.

7.1.1.3 SOC Team Interactions with TPs

Additional information might be required from TPs to identify the root causes of the event/alert or

gather additional contextual data, audit logs, explanations, etc. Only in 20% of cases no additional

information is required from TPs. In this case, the SOC team carries out their investigation (usually

taking between 1 hour and 2 days).

In 80% of cases, however, an interaction with TPs is required. Figure 7-4 illustrates the involved

steps:

Figure 7-4. Model 1: SOC Team Interactions with TPs

NOTE: We anticipate that this part of the process is critical, both in terms of risk exposure and

performance. It introduces a bottleneck due to fact that the SOC Team usually has to go through

multiple iterations with TPs in order to gather the required information: the quality and quantity of

the provided information is also another potential issue. A key problem is that there are no specific

policies or SLAs in place, with TPs, mandating criteria and obligations on how to effectively retrieve

and provide data to the SOC Team.

This part of the process usually starts with a request for information to a TP by the SOC Team, along

with an informal definition of the agreed timescale for responses.

In 40% of cases (on aggregated bases, over the various iterations between the TP and the SOC Team)

the TP does not respond in due time (usually after an agreed response period of 1-10 days, depending


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on the circumstances). In this case, a decision is made by the SOC Team to escalate the issue to the

Risk Management team (10% of cases) and deal with the escalation process (1-3 hours). This situation

triggers another process step, involving dealing with “TP Non Compliance” to agreed requests. The

process continues with the SOC Team asking again for the required information.

If the required information is provided by the TP (60% of cases, on aggregated basis) the model

captures various TP behaviours, based on observation provided by the SOC team:

Usually, 5-7 iterations are required with TPs, in order to gather the right information and

data;

The first iteration with TPs is critical: it can take between 1 and 10 days to get some

information back. This is due to various delays and overheads, for example the SOC team

having to identify the right TP people to interact with, delays in getting replays, various

redirections, etc.

The following iterations provide a better TP response time, usually between 1 and 3 days.

After receiving some data from the TP, the SOC team carries out their investigation (duration: 1 hour-

2 days). This might trigger the need to brief the Risk Management team, in 20% of cases (duration: 1-

3 hours).

Time is also spent to identify the recommended level category for the event/alert (1-2 hours).

The provided information might not satisfy the required quantity and quality criteria. This happens in

30% of cases: an additional request for information is made by the SOC Team.

If it satisfies the criteria, an additional SOC team investigation is carried out (duration: 1 hour - 1

day). This might raise the need to brief the Risk Management team again (10% of cases) and prepare

for the briefing (duration: 3 hours - 1 day).

If the incident category has been established (80% of cases), than a security incident is raised. In 10%

of cases the incident is a Major Security Incident.

Otherwise, the SOC Team decides if additional information is still required from TPs. As previously

mentioned, on average 5-7 iterations with the TP might need to take place before all the relevant

information is retrieved.

In case the required information has been provided, the process proceeds with the SOC Team final

assessment phase.

7.1.1.4 SOC Team Final Assessment

Figure 7-5 illustrates the steps involved in the SOC Team Final Assessment:


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Figure 7-5. Model 1: SOC Team Final Assessment

This usually involves an additional analysis activity by the SOC Team (duration: 4 hours -2 days),

followed by SOC team handling recommendations and agreements made with the Risk Management

team, which make take between 1 and 5 days.

The next process step involves the SOC Team providing recommendations about the level category

for the event/alert (duration: 2-4 hours). In 20% of cases the conclusion is that the event/alert is a false

positive. In this case, the procedure for handling false positives is followed.

Otherwise, in 80% of cases it is a security incident. In this case, in 95% of cases a security incident is

actually raised. The empirical data suggests that in 10% of cases a Major Security Incident is actually

raised.

In all other situations the event/alert is closed.

7.1.1.5 Event Closure

Figure 7-6 shows the involved steps:

Figure 7-6. Model 1: Event/Alert Closure

The process of closing an event/alert usually requires 1 hour – 2 days. It is followed by the writing of

a Report for the Risk Management Team, that usually takes between 1 hour and 1 day.


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7.1.1.6 Security Incident

Figure 7-7 shows the various process steps involved in case the event/alert has been classified as a

(IT) Security Incident:

Figure 7-7. Model 1: Security Incident

The actual process followed by the SOC team depends on the type of security incident:

Major Security Incident (SOC team’s Managed Incident): it is a critical incident that triggers

the second process, captured by Model 2 (Security Incident Management). This involves

raising a major security incident with the Risk Management team (duration: 1-2 hours),

recording the incident (0.5-1 hour) and producing an incident report (2-5 days), before

triggering the second process. On average there are 800-900 Major Security Incident per year;

Minor Security Incident: it usually requires raising an internal (SOC Team) minor security

incident (duration: 0.5-1 hour), recording the incident (0.5-1 hour) abd producing a minor

incident report (duration: 1-5 hours), usually requiring notifying the Risk Management Team

with a short email/document.

7.1.1.7 TP Non Compliance

The “TP Non Compliance” process is usually triggered if TP does not provide the required

information to the SOC Team in due time. Figure 7-8 shows the involved process steps:


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Figure 7-8. Model 1: TP Non Compliance

The SOC TEAM raises a TP Non Compliance Warning (duration: 1-2 hours), followed by reporting

the TP to the Risk Management Team (duration: 1-5 hours). This might be followed by an escalation

process to deal with the resolution of the problem or the acceptance of risk (this part is outside the

scope of this report).

7.1.1.8 Handling False Positives and Known Problems

This phase involves the handling of false positives and known problems, as shown in Figure 7-9:

Figure 7-9. Model 1: Handling False Positives and Known Problems


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If the event/alert is a false positive, it will be closed in 0.5-1 hour.

If initially the event/alert was classified as a known problem, a further assessment is made to

discriminate if it is a known problem with an acceptable risk (20% of cases) or if it is a false positive.

After this classification, the event/alert is closed, usually in 0.5-1 hour.

7.1.2 Metrics

This model has been built to carry out the investigations discussed in Section 3, specifically explore

the risk exposure and performance issues due to the SOC Team’s Event/Alert Processing &

Remediation Process. Metrics need to be put in place to provide measurements both for the current

situation and for what-if scenarios.

As such, the model has been instrumented with a set of metrics to convey outcomes in terms of risk

and performance. This includes:

Risk Indicators:

o Time to Process Events/Alerts in order to Identify (Minor and Major) Security

Incident: the longer the time to identify the nature of the event/alert, the longer the

organisation is exposed to potential risks, such as exploitation of privileged accounts,

spread of malware, exploitation of systems by attackers, etc;

o Time Spent in Iterations with TPs: this is a subset of the previous time. It specifically

measure the time that has been spent in interactions with TPs, being these a

bottleneck. Also in this case, the longer the time, the longer it takes to deal with the

event/alert, hence further exposing ServiceBizWorld to risks;

o Time Spent for Event/Alerts Closures: this is the time required to close an event/alert,

hence determining that there are no additional risks/issues for ServiceBizWorld;

o Time Spent to deal with TP Non Compliance Situations: this is the time spent to

process situations of TP non compliance i.e. when TPs do not provide the requested

information in due time. TP non compliance causes additional risk exposure for

ServiceBizWorld due to the additional delays to process events/alerts as well as

performance issues, due to the extra work carried out by the SOC Team to handle

them;

o Various Counters: counters have been introduced to count how many times an

event/alerts ends up as a (Major or Minor) Security Incident or as a Closed

Event/Alert, as well as many times there has been a TP Non Compliance issue.

Performance Indicators:

o Time Spent in Dealing with False Positives: this is the time required to identify false

positives and deal with them. The shorter it is the less time SOC Team resources are

used for this type of event/alert instead of focusing on potential security issues. This

time illustrates the impact on efficiency and performance;

o Time Spent in dealing with Known Problems: this is the time required to identify

known problems and dealing with them. The same comments made before, for false

positives, apply.

o Various Counters: counters have been introduced to count how many times an

event/alerts ends up as a false negative or a known problem.

Section 8 discusses how these metrics have been used to describe the outcomes for various

simulations.


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7.1.3 What-if Scenarios

This model, instantiated with the current empirical data, has been used to run simulations. The results

have been used to show the current state of risk exposure and performance. Section 8 presents these

outcomes.

A number of what-if scenarios have also been explored, based on ServiceBizWorld’s requests, aiming

to investigate the impact of making potential policy changes and/or additional investments in controls

as well the impact of changing threat landscapes:

1. Implications of making changes to Service Level Agreements (SLAs) with Third Parties (TPs);

2. Impact on risk exposure due to changes of the Threat Environment;

3. Impact of making (control) investments to improve Information Availability for TPs.

The next section provides more details about these what-if scenarios. Section 9 illustrates the results

obtained from simulations.

7.1.3.1 Impact of Changing SLAs for TPs

The experimental results discussed in Section 8 show that the interactions with TPs create a major

bottleneck within the Event/Alert Processing & Remediation process: this introduces delays that have

an overall negative impact on the performance and potentially increase the time required to make

decisions, hence having a negative impact on exposures to risks. This is particularly relevant in case

of Major Security Incident.

This what-if scenario aims at exploring the implications of improving the behaviour of TPs by means

of changing contractual SLAs, in particular about how they interact with the SOC Team to provide

information. Two main aspects have been investigated:

The impact of changing SLAs/Policies regulating interactions with TPs

What the best possible outcome is, if the TP interactions are streamlined and optimised

Ultimately, the desired outcome of this what-if analysis is to enable discussions with TPs to improve

the current situation and explore trade-offs involving Performance vs. Costs vs. Security Risks.

Various types of SLAs could have been explored and investigated. For the purpose of this scenario,

being the focus on the SOC Team – TP interactions, the following types of SLAs (and related

constraints) have been explored:

1. Provision of requested information to the SOC Team, within the agreed timeframe;

2. Maximum number of allowed TP iterations, for each event/alert, to collect the requested

information;

3. Quality and quantity of the information provided in TP responses;

4. Time to provide information to the SOC Team, for each iteration.

It is important to notice that, in this analysis, we only considered the case where the same class of

SLAs/Policies apply to all involved TPs. This might not necessarily be the case in other

contexts/scenarios. Security Analytics and related models can help to capture multiple classes of SLAs

and explore their implications.

Figure 7-10 illustrates four cases of potential SLAs, along with the related parameters for the Security

Analytics model, compared against the current situation:


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Cases TP Responding

in Time

(Aggregated)

Quality/

Quantity of Response

# TP Iterations Time to Provide data to the SOC Team, per Iteration

CURRENT 60% (single iteration:

92%)

70% 5-7 (average: 6) 1st: 1-10 days

>1: 1-3 days

CASE #1 70% (single iteration:

93.1%)

78% 4-6 (average: 5) 1st: 1-8 days

>1: 1-3 days


94.6%)

86% 3-5 (average: 4) 1st: 1-6 days

>1: 1-2 days


96.5%)

93% 2-4 (average: 3) 1st: 1-4 days

>1: 0.5-1.5 days


100%)

100% 1-2 1st: 1-2 days

>1: 1 hour-1 day

Figure 7-10. What-if Analysis: Changing SLAs with TPs

Each case introduces an improvement in the expected TP performance, compared to the current

situation. Case #4 potentially describes the best type of SLA that could be agreed with TPs i.e. the one

that should provide the best possible outcomes, all other aspects being the same.

For each of these cases, simulations have been carried out to determine the impact on the risk

exposure. Section 9 presents the results.

It is beyond the scope of this what-if scenario to indicate which specific controls and investments

should be put in place, to achieve these SLAs, from a TP perspective. We understand this involves

complex contractual agreements between the parties and changes in the way work is currently

organised with TPs.

However, in general, some of the improvements described in the SLAs can be achieved by optimising

the communications between the SOC Team and TPs and potentially deploying tools and solutions to

simplify and automate the involved critical process steps. This includes:

Defining templates about the type of requested information, for each specific managed event

and alert;

Defining scripts, at the TP site, to describe how and where to collect the relevant information,

to be provided to the SOC Team;

Providing ways to automate these scripts, for example by using monitoring tools and SIEM

solutions;

Deploying workflow management solutions spanning across the SOC Team and TPs, to track

the overall process of handling events/alerts and the information gathering activities.


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7.1.3.2 Impact of Changes of the Threat Environment

This what-if scenario aims at analysing the risk exposure implications in case of the worsening of the

threat landscape. What if, the threat environment gets worst and worst? What would be the impact, in

terms of risk exposure, if the number of new events/alerts to be handled by the process increases of

10%? Or 30%? Or 50%?

Various situations and scenarios might introduce sudden changes of the threat landscape:

Major social and economical events: this might include events such as the Olympic Games in

London 2012, major economical and financial crisis, etc. that could create a surge of social

engineering attacks and malware to exploit vulnerabilities and gather confidential information

from ServiceBizWorld’s employees;

Major changes in the ServiceBizWorld’s business model: this might include increasing the

number of services offered online and/or in the Cloud, hence potentially increasing the attack

surface and introducing new attack/exploitation opportunities for hackers.

In this scenario we consider the current event/alert processing situation as the baseline.

Simulations are carried out with the model to explore the implications, in terms of risk exposure, of

increasing the number of new events/alerts. Specifically the focus is on exploring the impact on the

time required to identify security incidents, including Major Security Incidents.

A desired outcome of this analysis is to enable discussion with TPs for Contingency Planning as well

as exploring suitable investment trade-offs between Costs (due to resources/personnel) vs. Security

Risks.

In this context it is important to identify critical thresholds, after which event/alert processing delays

start accumulating, hence exposing ServiceBizWorld to additional security risks.

The current bottleneck introduced by TP interactions has been the specific focus of this analysis.

Whilst ServiceBizWorld has direct control of the SOC Team and its incident management processes

and can flexibly adapt them to changes, this is not necessarily the case for TPs, especially for the

external service providers.

In this context, to effectively carry out the analysis, it has been necessary to introduce the concept of

Resources/Personnel into our model, related to the interactions between the SOC team and TPs. The

number of TP people (potentially part of local security teams) involved in each interaction to address

the SOC Team requests is limited: an increase in the workload might inevitably introduce delays.

It has been proven difficult to gather the specific information about the number of involved resources

(dealing with the event/alert processing activities) from the various TPs. This information is often

business confidential.

However, we can leverage Security Analytics and the model to make assumptions. The current model

for the Event/Alert Processing & Resolution process has been validated by the SOC Team and teh

Risk Management Team: it reflects the current solution.

It is possible to use it, make assumptions and derive the required information about resources

indirectly. Specifically, this involves:

Modelling the collective impact of the various TPs;

Modelling the TP allocation of resources/personnel in the context of their interactions with

the SOC Team;


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Doing a “reverse engineering” with the model, to indirectly determine a reasonable number

of TP resources/personnel that, once added to a new version of our model, produces the same

kind of outcomes – i.e. as in the current situation - in terms of risk exposure and

performance;

Allow for some “slack” in the usage of the current TP resources.

As previously mentioned, in the current modelled process, we focus on the interactions between TPs

and SOC Team, see Section 7.1.1.3, to obtain the data requested by the SOC Team.

The empirical data currently available suggests that the time required to get data from TPs is variable,

depending if it is the first iteration with a TP or a follow-up iteration:

1st Iteration: 1-10 days;

Follow-up Iterations: 1-3 days.

However, not all this time is spent by the involved TP resources in actively doing the work. A major

overhead is introduced to understand who to interact with, which information to retrieve and from

where, miscommunications, etc.

As such, the overall time required to provide a response by the TPs has been modelled in a more

accurate way, by splitting it in two parts:

Overhead time: this time does not really need resource allocations. It involves delays and

waiting time;

Actual work: this is the time spent to carry out the information gathering work, requiring the

utilisation of resources/people.

Figure 7-11 illustrates the assumption made for the current model (and validated by the SOC Team

and the Risk Management team) about splitting the current available time for “providing data to the

SOC Team” into the overhead and actual work times:

Time to Get Data from TPs in the 1st Iteration

Time to Get Data from TPs in the follow-up Iterations

CURRENT MODEL 1-10 days 1-3 days

MODEL

with TP RESOURCES

Overhead: 0.5 – 7.5 days

Actual work: 0.5 – 2.5 days

Overhead: 0.45 – 0.55 days

Actual Work: 0.5 – 2.5 days

Figure 7-11. What-if Analysis: Modelling Overhead and Actual Work time allocated to Resources

Of course different assumptions could have been made, by having more precise information from TPs.

It is beyond the scope of this report to explore the entire space of assumptions. The main purpose of

this what-if analysis is to illustrate the potential impact of changes of the landscape by using

reasonable assumptions and examples. The main goal is to use the simulation outcomes as additional

scientific data to enable informed follow-up discussions with TPs, in terms of Contingency Planning.

The current model of the Event/Alert Processing & Remediation Process has been extended, to factor

in the introduction of resources and the time breakdown, described in Figure 7-11.


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The updated model is shown in Figure 7-12:

Figure 7-12. What-if Analysis: Updated part of the Model to reflect Resources and Time Breakdown


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The only affected part of the model is the “Information Gathering Phase” phase, discussed in Section

7.1.1.3. Figure 7-13 shows the changes:

Figure 7-13. What-if Analysis: Specific updated part of the Model

As previously mentioned, this model has been used to carry out various experiments, with different

numbers of TP resources, to identify a reasonable number of resources that would produce results

consistent to the ones observed with the current “SOC event/alert processing & resolution” process.

Some slack in the utilisation of these TP resources has also been factored in.

The outcome of these experiments is that if 250 resources (people), spread across the various TPs

(along with the other assumptions mentioned before), are factored in, the updated Security Analytics

model provides results comparable to the ones obtained with the initial model (Figure 7-1). More

details are provided in Section 9, along with the outcomes of this what-if scenario. However, it is

important to notice that, in this context, the number of identified resources should be purely

considered as an internal Security Analytics mechanism to enable this type of analysis.

The updated model has then been used to explore different cases, involving changes in the threat

environment, in terms of an increase of the number of events/alerts received on daily basis, ranging

from +10% up to +60%. Figure 7-14 shows the different scenarios that have been analysed:

Case Events/Alerts per Day

CURRENT 35

CASE #1: +10% Events/Alerts 38




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Figure 7-14. Different Scenarios involving Changes of the Threat Landscape

For each of these cases, simulations have been carried out to determine the impact on the time to

identify a security incident (hence the impact on risk exposure) and the actual allocation of resources

over time, including situations where resources saturates and delays are introduced. Section 9 presents

the results.

It is important to notice that in case of resource saturations, the delays are likely to increase over

time. Hence results depend on the simulated time period. In the context of this what-if analysis, a

period of time of 6 months has been considered. We wanted to explore the implications for the

organisation of taking no actions during that entire period of time. The analysis can be tuned on a

different timeframe, based on needs.

7.1.3.3 Impact of Investments to Improve Information Availability for TPs

This what-if scenario is based on the previous two scenarios. Indeed, TP interactions are a bottleneck

and changes in the threat landscape can further negatively impact ServiceBizWorld’s exposures to

risks.

In case of a worsening threat landscape, TPs could inject an increased number of resources

(personnel) to cope with the additional workload: however, this does not make sense for a variety of

reasons, including practical and economic ones. Specifically, it would makes no sense for TPs to keep

investing in additional resources (personnel) without first addressing the root causes of the delays and

bottlenecks introduced in their interactions with the SOC team.

Discussions with the SOC Team and the Risk Management Team highlighted that one of the key root

causes of this problem is the “lack of information” and/or “complexity in retrieving it”. In other

words, TPs might need to spend considerable amounts of time in understanding how and where to

retrieve the requested information. This would account for most of the delays and overheads discussed

in the previous sections.

This is a complex problem to be addressed, as it involves legal, economical and contractual aspects.

New investments might need to be made by TPs and potentially the SOC Team; contracts and SLAs

might need to be modified.

However, the main goal of this what-if scenario is to illustrate the implications of making these

improvements and analyse the consequences, in particular in case of changes of the threat landscape

(worsening threat environment). These outcomes can be used as the starting point, i.e. as additional

evidence, for joint discussions, involving ServiceBizWorld, TPs and the SOC Team towards making

changes.

In this context, various controls have been considered as potential ways to improve the current

situation:


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Definition of SOC Team’s templates about the type of requested information, for each specific

managed event and alert. Definition of scripts, at the TP site, to describe how and where to

collect the relevant information, to be provided to the SOC Team;

Script automation coupled with advanced monitoring and correlation tools (e.g. SIEM

solutions [3], [4]);

Deployment of workflow management solutions (e.g. [9]) spanning across the SOC Team and

TPs, to track the overall process of handling events/alerts and the information gathering

activities.

A few assumptions have been made about the impact of introducing these controls on the overall

process, based on the technical capabilities and implications of the mentioned controls. Figure 7-15

illustrates three different cases that have been explored with Security Analytics simulations:

Investigation 1 - Cases

Additional Capabilities/Controls Parameters in the Model

(Information Gathering Phase)

CURRENT NONE Overhead: 1st Iteration: [0.5 days, 7.5 days]

Next Iterations: [0.45 days, 0.55 days]

Actual work: [0.5 days, 2.5 days]

CASE #1 - SOC Team’s templates defining the

types of required information

- Manual scripts, at the TP site, describing how to retrieve data

Overhead: 1st Iteration: [0.4 days, 6 days]


Actual work: [0.4 days, 2 days]

Note: Improvement of 20% compared to current situation

CASE #2 As above. In addition:

- Improved Monitoring Solutions at TP

sites

- Automated execution of scripts to

retrieve data

Overhead: 1st Iteration: [0.25 days, 3.75 days]





- Workflow automation spanning across

the SOC Team and TPs





Figure 7-15. What-if Investigation 1: Different Controls to Improve Information Availability

It has been estimated that, in Case 1, the introduction of templates and manual scripts will provide an

improvement of the overall TPs performances (see indicators in the table) of 20%, compared to the

current situation. The additional automation of the scripts, coupled with monitoring solutions (Case 2)

will introduce an improvement of 50%, compared to the current situation. Finally, the introduction of

workflow automation (Case 3) could introduce an improvement of 80%, compared to the current

situation.


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This what-if investigation, referred as investigation 1, still assumes that there will be 4-7 iterations

with TPs, for each information request coming from the SOC Team. This is the worst case scenario,

where no improvement happens in terms of reducing the number of iterations. This might be justified

with the fact that the improvement in speed-up the retrieval of information is not matched by

improvements in the communication with the SOC Team, hence still the need for multiple iterations.

A variant of this investigation, referred as investigation 2, has factored in the situation where the

number of required interactions with TPs is also affected, i.e. it progressively diminish by introducing

more sophisticated controls. Figure 7-16 illustrates the updated three what-if cases that have been

explored with Security Analytics simulations:


Additional Capabilities/Controls

Parameters in the Model


Number of TP Iterations (per event/alert)




5-7 iterations

(Average: 6)

CASE #1 - SOC Team’s templates

defining the types of

required information

- Manual scripts, at the TP

site, describing how to

retrieve data





4-6 iterations

(Average: 5)


- Improved Monitoring

Solutions at TP sites

- Automated execution of

scripts to retrieve data





2-3 iterations

(50% chances 2 or 3)


- Workflow automation

spanning across the SOC

Team and TPs





1-2 iterations


Figure 7-16. What-if Investigation 2: Introducing Improvements in the Number of TP Iterations

For each of the above 3 cases, both for Investigations 1 and 2, the parameters defined within the

model have been updated and a new version of the model generated. Each updated version of the

model has been used in simulations, to explore the specific implications and impact of threat

environments getting worst and worst.

Figure 7-17 shows the different threat environment situations that have been analysed, against each of

the 3 what-if cases (for investigations 1 and 2) discussed above:


Page 35 of 80


CURRENT 35

THREAT CASE #1: +10% Events/Alerts 38










Simulations have been carried out to determine the impact on the time to identify a security incident

(hence the impact on risk exposure) and the actual allocation of resources over time. Section 9

presents the results.


Page 36 of 80

7.2 Model 2: Incident Management Processes

The second model, related to the Incident Management Processes is shown in Figure 7-18. This

process is triggered by the process described in the first model, when Major Security Incidents are

identified by the SOC team.

The model captures the current process steps:

1. Notification of Major (IT) Security Incidents;

2. Various incident processing phases, including: Initial Assessment Phase, Information

Gathering from the Risk Assessment Team, TP Handling of the Incident Response;

3. Various possible outcomes of the execution of the process: TP Incident Remediation and Risk

Management.

It is important to notice that this process (and related model) is of secondary importance for the

purpose of the risk assessment analysis. It presents a subset of the issues already investigated in the

first process (e.g. TP interaction bottleneck): furthermore, it is not a critical process as it is only

triggered, on average, 800-900 times a year, i.e. each time a Major Security Incident is identified.

However, we believe that it is worth providing an explicit representation of this process and further

analysing the implications in terms of the additional risk exposure for ServiceBizWorld, when dealing

with the remediation of major security incidents. This analysis is very similar to the one carried out

for the first process.

Also in this case, the various process steps captured by the model are annotated with the empirical

data gathered from the SOC and Risk Management teams. They reflect the current situation in terms

of frequency of events, duration of process steps and likelihood of making certain decision. The

complete list of the empirical data used in this model is available in Appendix A.2.

When executed, this model simulates the arrival of Major (IT) Security Incidents and the various

processing steps, in order to determine the outcomes. The model has been instrumented with various

metrics, discussed in this section, to measure the impact in terms of risk exposure and performance.

The next sections describes in detail each of the key parts highlighted in the model.


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Figure 7-18. Model 2: Security Incident Management Process


Page 38 of 80

7.2.1 Modelled Process Areas

7.2.1.1 Events

Figure 7-19 shows that Major Security Incidents trigger the Incident Management Process, on average

800-900 times per year (about 3 incidents per day):

Figure 7-19. Model 2: Events for Security Incident Management Process

7.2.1.2 Initial Assessment Phase

Figure 7-20 shows the process steps involved in the incident assessment phase for Major Security

Incidents:

Figure 7-20. Model 2: Incident Assessment Phase

This phase involves an exchange of available information between the SOC Team and the Risk

Management team (duration: 1 hour -1 day) along with a joint analysis of the incident (duration: 1

hour – 1 day). These steps are followed by the SOC Team writing a summary report (duration: 1 hour-

4 hours).

This step might be followed by the need to collect additional information from the Risk Management

Team, in terms of priorities, risk mitigation practices and directions.

7.2.1.3 Information Gathering from Risk Management Team

Figure 7-21 describes the process steps involved in this phase:


Page 39 of 80

Figure 7-21. Model 2: Information Gathering from Risk Management Team

In 70% of cases, additional information about the security incident needs to be collected from the Risk

Management Team. In this case a request for additional information is made to the Risk Management

Team (duration: 1-4 hours). The requested information is usually provided in a timeframe of 1 hour -8

hours. This step is followed by an additional joint analysis involving the SOC Team and the Risk

Management Team (duration: 1 hour – 1 day).

This step is usually followed by an agreement, between the SOC Team and the Risk Management

team, about the remediation requirements, to handle the security incident. This step usually requires 1-

2 hours.

7.2.1.4 TP Handling of Incident Response


Figure 7-22. Model 2: TP Handling of Incident Response

This is the phase where a TP is in charge of handling their response to the security incident.

The SOC Team provides the TP with recommendations on how to handle the incident (duration: 1

hour – 2 days).

This step is potentially followed by a set of interactions between the SOC Team and the TP:

The TP provides a remediation document to the SOC Team (duration: 5 days -40 days);

The SOC Team carries out an analysis of the outcomes and the proposed mitigations

(duration: 4 hours -2 days);


Page 40 of 80

The SOC Team might decide that the TP response is inadequate. This happens in 45% of

cases. In this situation, an additional request for information is made by the SOC Team to the

TP (duration: 1-4 hours). In general, the empirical data suggests that there might be between 1

and 3 iterations before a satisfactory response is provided by the TP.

In case the TP response is satisfactory, a decision is made by the SOC Team about how to proceed. In

90% of cases the TP will remediate the incident. However in 10% of cases, this might not be possible

(e.g. it might not be obvious how to proceed, or the TP might not have the means/controls/tools to do

it). In this case the SOC Team will raise the risk and deal with related risk management steps.

7.2.1.5 TP Incident Remediation


Figure 7-23. Model 2: TP Incident Remediation

An incident report is written (duration: 2-3 days), followed by the actual remediation of the Security

Incident by TP (duration: 5 - 40 days)

7.2.1.6 Risk Management


Figure 7-24. Model 2: Risk Management

An incident report is written (duration: 2-5 days) followed by risk management steps (beyond the

scope of this modelling activity).

7.2.2 Metrics

Also this model has been built to carry out the investigations discussed in Section 3, specifically to

explore the risk exposure and performance issues due to the Incident Management Process.

The model has been instrumented with a set of metrics to convey outcomes in terms of risks. This

includes the following Risk Indicators:


Page 41 of 80

Time to Remediate an Incident: the longer the time to remediate the incident, the longer the

organisation is exposed to the potential risks, such as exploitation of privileged accounts,

spread of malware, exploitation of devices accessible via the Internet, etc;

Time Spent in Iterations with TPs: this is a subset of the previous time. It specifically

measures the time that has been spent in interactions with TPs. Also in this case, the longer

the time, the longer it takes to deal with the security incident, hence further exposing

ServiceBizWorld to risks;

Time Spent to Deal with Risk Management: this is the time to process the incident and

determine that it cannot be remediated, hence dealing with risk management;

Various Counters: for completeness, counters have been introduced to count how many times

an incident ends up to be remediated or in a Risk Management situation. However, their value

is obvious, given the simple nature of this model, based on the known frequency of the

security incidents (800-900 major security incidents per year) and the fact that 90% of them

will be remediated.

Section 8 discusses how these metrics have been used to describe the outcomes of the simulations.

7.2.3 What-If Scenarios

7.2.3.1 Impact of Investments to Improve the Process Performance

The current Security Incident Management Process is relatively simple, compared to the SOC

Event/Alert Processing & Remediation process. In addition it is not very critical, as (on average) it is

executed 800-900 times per year, when Major IT Security Incidents occurs.

However this process (similarly to the other one) is affected by the potential bottleneck introduced by

TP interactions. Furthermore, the current empirical data reveals that it could take up to 40 days for

TPs to remediate incidents. This is a very large period of time, that can potentially expose

ServiceBizWorld to additional risks (such as exploitation of the root causes of the incident).

What-if investments are made to improve the current situations, primarily to reduce the involved

delays? Despite the process being simple and the outcomes intuitive, it still make sense to explore the

types of investments and controls that could be deployed and assess their impact.

Two kind of issues need to be addressed.

The first issue is related to the “Handling of the Incident Response” phase. Various TP interactions

might occur (up to 3), each of them potentially requiring long periods of time to get TP’s remediation

documents (potentially up to 40 days each).

In this case various kinds of investments and solutions could be considered to potentially improve the

performance. For the purpose of this what-if analysis, the following types of solutions have been

considered, each of them with an increasing level of impact and automation:

Remediation Templates to describe common remediation activities for known, recurrent

security incidents;

Knowledge-base and collaborative solutions (such as [7]) to provide guidance about

acceptable remediation plans and track their evolution against agreed SLAs/deadlines;

Incident Response Plan solutions (such as [8]) to automate the overall process of handling the

definition of remediation plans.

The second issue is related the “TP Incident Remediation” phase. As mentioned above, it might

require a long period of time for TPs to remediate to incidents (up to 40 days).


Page 42 of 80

Also in this case various kinds of investments and solutions could be considered to potentially

improve the performance. For the purpose of this what-if analysis, the following types of solutions

have been considered, each of them with an increasing level of impact and automation:

Manual templates and scripts to carry out remediation activities for known, recurrent

security incidents;

Automated templates, knowledge-base and scripts to carry out remediation activities;

Change management tools and solutions to track and automate the overall remediation

activities (such as [9]).

The combined deployment of these controls and solutions at the TP sides is likely to affect the

following aspects:

Number of required iterations with TPs to obtain a satisfactory response in terms of

remediation plans/documents;

Time required by TPs to provide the remediation plans/documents;

Time required by TPs to remediate the security incidents.

Figure 7-25 shows the cases and assumptions that have been explored in this what-if analysis

involving the deployment of combinations of the above controls:

Cases Additional Capabilities/Controls Parameters in the Model

CURRENT NONE TP Handling of Incidence Response

Time to Produce Remediation Documents:

[5 days, 40 days]

Num TP Iterations: (1,3)

TP Incident Remediation

Time to TP Incident Remediation:

[5 days, 40 days]

CASE #1 TP Handling of Incidence Response

- Remediation Templates


- Manual templates and scripts

TP Handling of Incidence Response


[4 days, 32 days]




[4 days, 32 days]

Overall Improvement: 20%


- Knowledge-base and Collaborative

Solutions


- Automated templates, Knowledge base



[2.5 days, 20 days]



Page 43 of 80

and scripts TP Incident Remediation


[2.5 days, 20 days]



- Incident Response plan solutions


- Change Management Tools and

Solutions



[1 day, 8 days]

Num TP Iterations: (1)



[1 day, 8 days]


Figure 7-25. What-if Scenarios: Different Controls to Improve Process Performance

Simulations have been carried out to determine the impact on the time to remediate an incident, the

time to decide to do risk management and the time spent in TP interactions. These metrics give an

indication both of the performance of the process and the potential risk exposure for ServiceBizWorls.

Section 9 presents the results.


Page 44 of 80

8 Results Regarding Current State

This section presents the various analytic results that have been obtained by running simulations with

model 1 (Event/Alert Processing & Remediation Process) and model 2 (Security Incident

Management Process) to illustrate the ServiceBizWorld’s risk exposure and performance

implications, due to the current processes. These results, along with the related models, have been

validated in various discussions with the SOC Team and the Risk Management Team and used as the

foundation for what-if analysis (presented in Section 9).

8.1 Model 1: Events/Alerts Processing and Resolution

Model 1 (Event/Alert Processing & Remediation Process) has been instantiated with the available

empirical data discussed in Section 7 and used in simulations to explore the current implications in

terms of risks and performance. The outcomes are conveyed by means of the agreed set of metrics

(see Section 7).

Figure 8-1 shows the distribution of the time required to identify a security incident, within the current

process:

Figure 8-1. Distribution of Time to Identify Security Incidents

The graph shows that there is lot of variability in the time required to identify security incidents, in the

[2 days to 50-60 days] range. Most occurrences are in the [5-40] day range. Just a small percentage

requires a period of time less than 9-10 days, reflecting the case where no TP interactions are

required.

This graph illustrates the potential impact on ServiceBizWorld’s risk exposure due to the delays

introduced to identify a security incident and act on it. The very long involved time might give

opportunities to attackers for further exploitations.

This is particularly important for Major Security Incidents, as the same time distribution applies, see

Figure 8-2:

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Figure 8-2. Distribution of Time to Identify Major Security Incidents

It is important to notice that to the time shown in Figure 8.2, additional time has to be added before a

Major Security Incident is actually remediated, as discussed in the next section. This further

highlights the potential risk exposure for the company.

The SOC Team needs to process about 12000 events/alerts per year, of which 800-900 are classified

as Major Security Incidents. As there is currently no specific process differentiation, their handling is

affected by the processing workload introduced by the other events/alerts. This might be an area

subject to further exploration and analysis.

A critical aspect, confirmed by this analysis, is the impact that TP Interactions have on the overall

results, as shown in Figure 8-3:

Figure 8-3. Distribution of Time Spent in TP Iterations

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Page 46 of 80

This time distribution has a wide spread, with about 80% of cases ranging between 12 and 50 days.

This creates a bottleneck that affects the entire process and has a negative impact not only on the

overall performance but also on ServiceBizWorld’s risk exposure.

Figure 8-4 shows the time to deal with “TP non compliance”, i.e. the time to track and handle TP

failures to provide the required information in due time to the SOC Team:

Figure 8-4. Distribution of Time for TP Non Compliance

Given the nature of the current process, TP non compliance issues can be raised by the SOC Team at

any time during the execution of the process itself. Once again, the graph shows the potential large

delays in identifying situations that affect risk exposure and performance. This is a direct consequence

of the potential large period of time spent in the process to deal with TP Iterations.

Figure 8-5 shows the distribution of the time to process events/alerts that ends up in their closure:

Figure 8-5. Distribution of Time to Process the Closure of Events/Alerts

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Page 47 of 80

This graph clearly shows that events/alerts can be closed in 2-10 days, if the SOC Team has the

information required for their processing and no TP interaction is required. This situation however

covers about 25% of the cases. If the SOC Team has to interact with TPs, the required time further

increases, up to 50-60 days.

Figure 8-6 shows the distribution of the time required by the SOC Team to process false positives:

Figure 8-6. Distribution of Time to Process False Positives

The graph shows that, in about 40% of cases, false positives are identified in the early stages of the

process and dealt within 1-2 days. This is an encouraging result in terms of performance, in the sense

that the time required for their processing is minimal, and the SOC Team resources can be used for

other tasks. However, about 40% of false positives are handled in the [25,50] days range, reflecting

the fact that 20% of the processed events/alerts are classified as false positives only after TP

interactions.

Figure 8-7 shows the distribution of the time to handle known problems:

Figure 8-7. Distribution of Time to Handle Known Problems

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Page 48 of 80

This time is in the range of [5,50] hours (i.e. max 2 days) reflecting the fact that all known problems

are identified in the early stages of the process and efficiently managed by the SOC Team.

Finally, Figure 8-8 provides a breakdown of the types of outcomes of the process, based on various

counters (metrics) introduced in the model:

Summary: Impact of Various Types of Outcomes

0 1000 2000 3000 4000 5000 6000 7000 8000

counterTPNonCompliance

counterMinorSecurityIncident

counterMajorSecurityIncident

counterEvent/AlertClosure

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counterClosureKnownProblem

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counterMajorSecurityIncident

counterEvent/AlertClosure

counterClosureFalsePositive

counterClosureKnownProblem

Figure 8-8. Breakdown of Counters

This figure shows that about 65% of the events/alerts are eventually classified as minor security

incidents. TP Non compliance affects almost 35% of the processed events/alerts, reflecting the

empirical data introduced in the model. False positives account for 20-25% of the overall

events/alerts.

8.1.1 Summary

The analysis of the current situation highlights the fact that TP interactions have a major impact on

ServiceBizWorld’s risk exposures, along with potential performance implications. This issue is well

known by the SOC Team and the Risk Management Team: this analysis confirms it by quantifying

the implications and adding scientific evidence.

The analysis shows that TP interactions usually account for 60-70% of the involved processing time.

The delay introduced by these interactions is reflected in all metrics analysed in the simulations.

To conclude, the impact in terms of additional exposure to risks is evident, due to the introduced

delays: this is particular important in the context of Major Security Incidents.

Section 9 illustrates, by means of what-if analysis, how the current situation could be improved by

introducing specific SLAs for TPs, along with making investments in specific controls/solutions.


Page 49 of 80

8.2 Model 2: Incident Management Process

Model 2 (Security Incident Management Process) has been instantiated with the available empirical

data discussed in Section 7 and used in simulations to explore the current implications in terms of

risks and performance. The outcomes are conveyed by means of the agreed set of metrics (see Section

7).

As mentioned in Section 7, the Security Incident Management Process is activated, on average, 800-

900 times per year (3 times on daily basis), to deal with Major Security Incidents.

This is a much simpler process that the one involving the handling of events/alerts but it is affected by

similar issues.

Figure 8-9 shows the distribution of the time to remediate a Major Security Incident:

Figure 8-9. Distribution of Time to Remediate a Major Security Incident

The result shows a huge variability in the time required to remediate a major security incident,

ranging from a few days up to 5 months. The outcomes directly reflect the empirical data available.

The main issues are around the potential delays introduced by TP iterations to deal with the incident

response and the actual remediation time required by TPs, that might take up to 40 days.

This reflects the complex nature of dealing with this type of incidents as well as specific issues within

TP organisations to timely react and remediate them.

The implications, in terms of risk exposure for ServiceWorldBiz, are evident: the potential critical

vulnerabilities and issues that are the root cause of the security incident might be exploited by

attackers before they are remediated.

Figure 8-10 shows the distribution of the time to Risk Management, i.e. the case when the incident

cannot be remediated and the involved risk has to be handled:

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Page 50 of 80

Figure 8-10. Distribution of Time to Risk Management

The graph shows that it might take up to 4 months to conclude that the major security incident cannot

be remediated and the risk has to be managed. This is again a reflection of the time spent in TP

iterations.

Finally, Figure 8-11 shows the distribution of time that is actually spent in TP iterations to handle the

incident response:

Figure 8-11. Distribution of Time spent in TP Iterations

The result confirms that it might take up to 4 months to interact with TPs, to handle the incident

response. This influences the other process outcomes.

8.2.1 Summary

The analysis of the current situation confirms the fact that, also in this process, TP interactions have a

major impact on ServiceBizWorld’s risk exposure, along with potential performance implications.

These results reinforce the findings of the analysis carried out in the first process.

Noticeably, it might take up to 7 months to fully remediate a major security incident, if we consider

the time required to identify the security incident and the actual time required to mitigate it.

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Page 51 of 80

There are potential margins for improvement involving investments in controls/solutions and

streamlining/optimising the activities carried out by TPs. A few potential options are explored in

Section 9, by means of a what-if analysis.


Page 52 of 80

9 Results for What-If Scenarios

This section presents the experimental results obtained from the analysis of what-if scenarios, for both

models. The full description of the what-if scenarios is available in Section 7.

9.1 Model 1: Security Event/Alert Processing and Resolution

9.1.1 Impact of Changing SLAs for TPs

This what-if analysis aims at exploring the impact of changing SLAs for TPs, based on the set of

cases described in Section 7. The goal is to explore the improvement that this could bring by reducing

the bottleneck with TPs.

Figure 9-1 summarises the four cases that have been explored:

Cases TP Responding

in Time

(Aggregated)

Quality/

Quantity of Response

# TP Iterations Time to Provide data to the SOC Team, per Iteration

CURRENT 60% (single iteration:

92%)

70% 5-7 (average: 6) 1st: 1-10 days

>1: 1-3 days


93.1%)

78% 4-6 (average: 5) 1st: 1-8 days

>1: 1-3 days


94.6%)

86% 3-5 (average: 4) 1st: 1-6 days

>1: 1-2 days


96.5%)

93% 2-4 (average: 3) 1st: 1-4 days

>1: 0.5-1.5 days


100%)

100% 1-2 1st: 1-2 days

>1: 1 hour-1 day

Figure 9-1. What-if Analysis: Changing SLAs with TPs

For each case, comparative graphs (for each of the agreed metrics) have been created, to illustrate the

impact of the SLA changes against the current situation.

Figure 9-2 shows the impact that different SLAs have on the time to identify security incidents:


Page 53 of 80

Figure 9-2. Comparative Analysis of Time to identify Security Incidents – based on different SLAs

The graph shows a major improvement in the overall time required to identify a security incident

depending on the SLA case.

In the best case scenario (Case 4), the required time is almost 1/3 of the current one, with an average

of 6-15 days compared to the current 20-45 days. Further improvements could be made in other parts

of the process, including the initial and final assessment phases carried out by the SOC Team.

Being able to reduce this timeframe is important as it further reduces ServiceBizWorld’s risk

exposure to security incident, in particular for Major Security Incidents (e.g., exposures of company’s

systems to attacks, exploitation of privileged accounts, etc.). The sooner the root cause of the incident

is identified, the sooner the remediation process can start and the risk be mitigated.

Figure 9-3 shows the specific impact that different SLAs have on the time to identify major security

incidents:

Figure 9-3. Comparative Analysis of Time to identify Major Security Incidents – based on different SLAs

The graphs show similar patterns and improvements to the ones shown in Figure 9-2. The graph

highlights that it takes at least 6-9 days to identify Major Security Incidents, independently from the

SLA improvements. This is due to the fact that, independently from the TP interactions, time is spent

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Page 54 of 80

by the SOC Team to carry out various analysis steps: this aspect could be potentially improved by

further streamlining the SOC Team activities. Furthermore, the overall time is also affected by the

need to produce Incident Reports and recording the incident: it currently takes an additional 1 day.

Figure 9-4 shows the specific impact that different SLAs have on the time spent in TP iterations:

Figure 9-4. Comparative Analysis of Time Spent in TP Iterations – based on different SLAs

The graphs shows that this time can be drastically reduced, at least for Cases 3 and 4 (1/3 and 1/5

respectively of the current time). The reduction of this time positively affects the overall process as

currently TP interactions are the major bottleneck.

Figure 9-5 shows the specific impact that different SLAs have on the time to report TP non

compliance:

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Page 55 of 80

Figure 9-5. Comparative Analysis of Time to Report TP Non Compliance – based on different SLAs

The graph shows improvements, nevertheless the time to report TP non compliance is still affected by

the fact that violations can happen at any time in the interaction process with TPs. Apart from the

ideal Case 4, where the SLA assures that there should be no violations, Case 3 highlights that the

reporting of “TP non compliance” situations can still happen in a range of [2,30] days, reflecting the

empirical data in the model. Further improvements can be introduced by reducing the deadlines by

which the TPs are requested to provide the information to the SOC Team (after which the SOC Team

escalates the violations to the Risk Management Team).

Figure 9-6 shows the specific impact that different SLAs have on the time to close events/alerts:

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Page 56 of 80

Figure 9-6. Comparative Analysis of Time to Close Events/Alerts – based on different SLAs

This graph shows a similar improvement trend to the ones shown before, based on better and better

SLAs. In the best case, events/alerts can be closed in 3-18 days, against the current 24-60 days.

Figure 9-7 shows the specific impact that different SLAs have on the time to close false positives:

Figure 9-7. Comparative Analysis of Time to Close False Positives – based on different SLAs

This figure shows the specific impact of the SLA changes on handling false positives. SLAs changes

have no impact if the false positives are discovered in the early stages of the process (10% of cases),

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Page 57 of 80

and/or if no TP interactions are involved. In this case the closure time still ranges between 1 and 3

days. However, the major impact is when the false positives are discovered after TP interactions. In

the best case, the time to handle them is in the [3,18] day range, a major improvement compared to

the current [24,50] days.

In this context, SLA improvements have a major productivity impact, as less time is spent to process

false positives and resources can be utilise to handle other types of events/alerts and incidents.

Finally, Figure 9-8 shows the impact that SLAs have on different counters used as metrics in the

model:

Figure 9-8. Comparative Analysis of Counters – based on different SLAs

As expected, only the number of “TP Non Compliance” is directly affected by SLA changes. All

other events (and related counters) are unaffected.

9.1.1.1 Summary

The analysis of this what-if scenario shows that changes of SLAs for TPs can have a major impact in

reducing risks for ServiceBizWorld and potentially improving productivity. This is particularly true in

case of: handling security incidents where the time to identify them can be reduced from the current

[20, 45] days to [6,15] days; handling false positives in [3,18] days, compared to the current [24,60]

days.

It is beyond the scope of this analysis to suggest specific controls and contractual agreements with

TPs in order to achieve the SLAs highlighted in the various cases.

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Num Minor Security Incident

Num TP Non Compliance

CURRENT

CASE1

CASE2

CASE3

CASE4


Page 58 of 80

9.1.2 Impact of Changes of the Threat Environment

This what-if analysis aims at analysing the impact of changes of the Threat Environment, based on the

set of cases described in Section 7.

The goal is to explore the implications in terms of risk exposure for ServiceBizWorld in case the

threat landscape gets worst. Specifically, the analysis focuses on the impact of the bottleneck

introduced by TP interactions.

The updated Security Analytics model, factoring in resources/personnel, has been used in simulations

to explore the implications in terms of the time required to identify security incidents (including major

security incidents) and related allocation of resources, to identify saturation points.

Figure 9-9 shows the various cases that have been explored, each of them involving changes of the

threat environment. This results in an increase of the number of new events/alerts to be processed on

daily basis:


CURRENT 35








As already mentioned in Section 7, it is important to notice that in case of resource saturations, the

delays are likely to increase over time. Hence results depend on the simulated time period. In the

context of this what-if analysis, a period of time of 6 months has been considered. We wanted to

explore the implications for the organisation of taking no actions during that entire period of time.

This note applies to all the what-if scenarios discussed in this section, involving allocation of

resources/personnel. The analysis can be tuned on a different timeframe, depending on needs and

requirements.

Based on the assumptions discussed in Section 7, Figure 9-10 shows the current situation in terms of

time distribution to identify security incidents and the (predicted) allocation of TP resources, over time

(in days):


Page 59 of 80

Figure 9-10. Current Situation – Time to identify Security Incidents and TP Resource Allocation

Figure 9-11 shows the predicted impact of changes of the threat environment, for Case 1 (+10%

events):

Figure 9-11. Case 1 – Time to identify Security Incidents and TP Resource Allocation


events):



events):

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Page 60 of 80



events):



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Page 61 of 80


Figures 9-11, 9-16 show the increasing negative impact that the worsening of the threat landscape has

of the overall process, in particular with regards to the “time to identify security incidents”. These

simulations highlight that the process copes well in case of an increase of events/alerts up to 20%: in

the simulated timeframe (6 months) the time to identify incidents is not affected and the allocated TP

resources. These resources can deal with the increased workload without major delays, despite the

fact that they increasingly saturate. Some initial delays are already noticeable with an increase of 30%

of the events/alerts.

To summarise, Figure 9-17 provides a comparative analysis of the time to identify security incidents,

across all Cases explored in this what-if analysis:

Figure 9-17. Comparative Analysis – Time to identify Security Incidents for various Cases

An increase of 30% of alerts/events or more causes the saturation of the allocated TP resources: TPs

will increasingly have problems to cope with the workload. This is reflected in the figure, comparing

the various distributions of time to identify security incidents. More and more time is required to deal

with events/incidents. Case 5 and 6 explicitly show the impact of the accumulation of delays, due to

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Page 62 of 80

the resource saturation (in the considered timeframe): the required time to process incidents can

exceed 75 days.

It is important to notice that these outcomes reflect the assumptions initially made in Section 7- in the

situation where no changes are made in the 6 months timeframe. These results are potentially

sensitive to the parameters used in the model. However, these results provide a qualitative analysis of

the negative impact that changes in the threat environment have on the overall process and the

consequences for ServiceBizWorld risk exposure (all other conditions being the same): the more the

threat environment get worst, the more time is required to process events/alerts, hence

ServiceBizWorld is exposed to additional risks.

Finally, Figure 9-18 provides a summary of the potential additional risk exposures for

ServiceBizWorld, by means of a comparative view for the different threat environment cases. A green

box indicates that the risk exposure situation is comparable to the current one (or improved). An

orange box indicates that the risk exposure situation is potentially getting worst (moving towards TP

resource saturation and/or increase of the time to deal with security incidents). A red box indicates a

potential critical risk exposure for ServiceBizWorld, involving major saturation of TP resources and

time delays:

Current Case 1 (+10%) Case 2 (+20%) Case 3 (+30%) Case 4 (+40%) Case 5 (+50%) Case 6 (+60%)

Potential Impact

on Risk Exposure

Figure 9-18. Comparative Analysis – Risk Exposure due to Changes of the Threat Environment

This notation is also used in the next what-if scenario.

9.1.2.1 Summary

The analysis of this what-if scenario illustrates (in a qualitative way) the potential implications for the

Event/Alert Processing & Resolution process in case of the worsening of the threat landscape.

The bottleneck introduced by TP interactions is critical. Simulations, based on assumptions made in

terms of available TP resources, illustrates that the situation can rapidly get worse and worse if the

number of new events/alerts to be processed (on daily bases) increases more than 20%. This has a

negative impact on ServiceBizWorld’s risk exposure, due to the increased time to identify security

incidents, in particular Major Security Incidents.

This analysis provides additional evidence to ServiceBizWorld and the SOC Team to enable

contingency planning discussions with TPs.


Page 63 of 80

9.1.3 Impact of Investments to Improve Information Availability for TPs

The previous what-if analysis shows that the available TP resources can quickly saturate in case of

changes of the threat landscape and have a major negative impact in terms of additional risk exposure

for ServiceBizWorld.

As discussed in Section 7, it does not make sense for TPs to increase the number of resources, without

first addressing the root causes of the delays introduced in their interactions with the SOC Team. This

primarily means improving the way they gather the information requested by the SOC Team. Based

on input received from the SOC Team and the Risk Management Team, the major causes of the

problem are: (1) the lack of information and (2) how to retrieve the required data.

This what-if analysis aims at analysing the impact of making investments to improve information

availability for TPs. Various types of investments are possible. Figure 9-19 shows the cases that have

been analysed, in a first investigation, as discussed in Section 7:


Additional Capabilities/Controls Parameters in the Model





CASE #1 - SOC Team’s templates defining the

types of required information

- Manual scripts, at the TP site, describing how to retrieve data






- Improved Monitoring Solutions at TP

sites

- Automated execution of scripts to

retrieve data






- Workflow automation spanning across

the SOC Team and TPs





Figure 9-19. What-if Investigation 1: Different Controls to Improve Information Availability

This first investigation assumes that the number of involved iterations with TPs is the same as in the

current situation.

As discussed in Section 7, for each of the 3 investment cases shown in Figure 9-19, models have been

built and used in simulations to predict the outcomes (i.e. time to identify a security incident and

resource allocation) for the different threat environment scenarios shown in the following Figure 9-20:


Page 64 of 80


CURRENT 35











Related to the Investigation 1- Case 1 (Figure 9-19: definition of templates and manual scripts, with

an overall performance improvement of 20%), Figure 9-21 compares the impact that different threat

scenarios have on the time to identify security incidents:


Page 65 of 80

Figure 9-21. What-if Analysis – Case 1: Comparative View based on Changes of the Threat Landscape

This figure shows that, based on simulations, the controls and solutions defined in Case 1 introduce a

major improvement, compared to the situation discussed in the previous what-if scenario.

Basically, there are no major delays in the time to identify security incidents in case the number of

events/alerts increases up to 50% (on daily basis). However, after that threshold, the situation quickly

deteriorates, due to the saturation of the TP resources.

This is a noticeable improvement, compared to the current process and controls, where the situation

can rapidly get worst if the number of new events/alerts to be processed increases more than 20% on

daily basis (see the what-if analysis in the previous section).

Related to the Investigation 1- Case 2 (Figure 9-19: use of monitoring tools and script automation,

with an overall performance improvement of 50%), Figure 9-22 compares the impact that different

threat scenarios have on the time to identify security incidents:


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Page 66 of 80

This figure shows that, based on simulations, the controls and solutions defined in Case 2 introduce an

even bigger improvement. There are no noticeable changes of the time to identify security incident in

case the number of events/alerts increases up to 90% (on daily basis). The results also show a

reduction of the overall time to identify a security incident, consistently with the assumptions that

have been made.

Finally, related to the Investigation 1 - Case 3 (Figure 9-19: use of automated workflows, with an

overall performance improvement of 80%), Figure 9-23 compares the impact that different threat

scenarios have on the time to identify security incidents:


This figure confirms and consolidates the previous trend. There are no noticeable changes of the time

to identify security incident in case the number of events/alerts increases up to 90% (on daily basis).

The results also show a significant reduction of the overall time to identify a security incident,

consistently with the assumptions that have been made.


ServiceWorldBiz, by means of a comparative view of the different threat environment cases. A green




potential critical risk exposure for the company, involving major saturation of TP resources and time

delays:

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Page 67 of 80

CURRENT

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CUR-

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3


It is important to notice, that in this first investigation, it was assumed that the new controls and

solutions do not affect the overall number of iterations with a TP required to gather the information

(requested by the SOC Team). In other words, this number of TP iterations (i.e. 4-7, with an average

of 5 iterations for each processed event/alert) is exactly the same as in the current process. The

additional investments primarily reduce the time spent by TP resources to deal with information

requests from the SOC team.

The next investigation, i.e. Investigation 2, considers a more optimistic scenario where the

improvement of the information availability for TPs has also a positive impact on the number of TP

iterations, by progressively reducing it, for each analysed case.

Figure 9-25 shows the cases that have been analysed, in the second investigation, as discussed in

Section 7:


Additional Capabilities/Controls

Parameters in the Model


Number of TP Iterations (per event/alert)




5-7 iterations

(Average: 6)

CASE #1 - SOC Team’s templates

defining the types of

required information

- Manual scripts, at the TP

site, describing how to

retrieve data





4-6 iterations

(Average: 5)


- Improved Monitoring

Solutions at TP sites

- Automated execution of

scripts to retrieve data





2-3 iterations



Page 68 of 80


- Workflow automation

spanning across the SOC

Team and TPs





1-2 iterations


Figure 9-25. What-if Investigation 2: Introducing Improvements in the Number of TP Iterations

Again, as discussed in Section 7, for each of the 3 investment cases shown in Figure 9-25, models

have been built and used in simulations to predict the outcomes (i.e. time to identify a security

incident and resource allocation) for the different threat scenarios shown in Figure 9-20.

Related to the Investigation 2 - Case 1 (Figure 9-25: definition of templates and manual scripts, with

an overall performance improvement of 20% and 4-6 TP iterations per event/alert), Figure 9-26

compares the impact that different threat scenarios have on the time to identify security incidents:


The results show a neat improvement in terms of the overall performance, across the various threat

environment scenarios, compared to the results shown in Figure 9-21, in particular for those cases

involving an increase of the number of alerts/events greater than 60%. This is due to the reduced

number of interactions with TPs. However simulations show that the TP resources still saturates for

increases of number of events/alerts greater than 80% and delays are introduced in the process.

Related to the Investigation 2 - Case 2 (Figure 9-25: use of monitoring tools and script automation,

with an overall performance improvement of 50% and 2-3 TP iterations per event/alert), Figure 9-27

compares the impact that different threat scenarios have on the time to identify security incidents:

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Page 69 of 80


These results are quite positive. If the deployed controls effectively reduce the number of TP

iterations as assumed, no noticeable delays and TP resource saturations are observed, even in the

worst case threat environment considered in this what-if scenario (90% increase of events/alerts).

The number of TP iterations indeed decreases the overall time to identify security incidents of about

20-30%, compared to the times shown in Figure 9-27.

Related to the Investigation 2 - Case 3 (Figure 9-25: use of automated workflows, with an overall

performance improvement of 70% and 1-2 TP iterations per event/alert), Figure 9-28 compares the

impact that different threat scenarios have on the time to identify security incidents:

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Page 70 of 80


Also these results confirm the trends shown in Figure 9-23. If the deployed controls effectively reduce

the number of TP iterations as assumed, no noticeable delays and TP resource saturations are

observed, even in the worst case threat environment considered in this what-if scenario (90% increase

of events/alerts).

The number of TP iterations further decreases the overall time to identify security incidents of about

40%, compared to the times shown in Figure 9-23.


ServiceBizWorld, by means of a comparative view of the different threat environment cases. A green




potential critical risk exposure for the company, involving major saturation of TP resources and time

delays:

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Page 71 of 80

CURRENT

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CURRENT

Case 1

Case 2

Case 3


We can notice a sensible improvement in the context of Case 1, where the situation is now critical

only when the increase of events/alerts is greater than 80%. Simulations highlight the saturation of TP

resources only in that situation. In all other cases (in the simulated timeframe) there are no resource

saturation and delays.

9.1.3.1 Summary

The analysis of this what-if scenario illustrates (in a qualitative way) that by tackling the issues related

to TP information availability, it is possible to get major improvements in the overall performance of

the process, and contain the ServiceBizWorld’s risk exposure to situations where the threat landscape

deteriorates.

Based on the assumption made, the simple deployment of templates with just manual scripts improves

the situation: it ensures that the overall process can cope with an increase of 60% of the current

number of events/alerts, without degradations and negative impacts of ServiceBizWorld’s risk

exposure: the increase can be of 80% if the controls also sensibly reduce the number of TP iterations.

The deployment of templates and automated scripts or automated workflows, ensures that the overall

process can cope with an increase of 90% (or more) of the current number of events/alerts, without

degradations and negative impacts of the company’s risk exposure.

Again, the main goal of this analysis is to provide additional evidence to ServiceBizWorld and the

SOC Team to enable contingency planning discussions with TPs.


Page 72 of 80

9.2 Model 2: Incident Management Process

9.2.1 Impact of Investments to Improve the Process Performance

This what-if analysis aims at investigating the impact of making investments in controls and solutions,

based on the set of cases described in Section 7. The goal is to explore the improvement in the process

performance and related risk reductions, by both reducing the bottleneck introduced by TPs and the

involved remediation time. Figure 9-30 summarises the three cases that have been explored (against

the current situation):

Cases Additional Capabilities/Controls Parameters in the Model

CURRENT NONE TP Handling of Incidence Response


[5 days, 40 days]




[5 days, 40 days]


- Remediation Templates


- Manual templates and scripts



[4 days, 32 days]




[4 days, 32 days]



- Knowledge-base and Collaborative

Solutions


- Automated templates, Knowledge base

and scripts



[2.5 days, 20 days]




[2.5 days, 20 days]



- Incident Response plan solutions




[1 day, 8 days]

Num TP Iterations: (1)


Page 73 of 80

- Change Management Tools and

Solutions TP Incident Remediation


[1 day, 8 days]


Figure 9-30. What-if Scenarios: Different Controls to Improve Process Performance

For each case, comparative graphs have been created, to illustrate the impact of the additional controls

and solution against the current situation. Specifically, simulations have been carried out to explore

the implications in terms of “time to remediate a major security incident” and “time spent in TP

Iterations”.

Figure 9-31 shows the impact that the new controls have on the time to remediate a major security

incident, for all the above three cases:

Figure 9-31. Comparative Analysis: Time to Remediate Major Security Incidents

Based on the assumptions made, in case 3 (involving automated solutions and controls) the time to

remediate a major security incident is in the range of [7,21] days, compared to the [21,150 days that

might take in the current situation. The improvements in terms of performance and reduction of risk

exposure for ServiceBizWorld are evident.

Interestingly, it takes at least 7 days to remediate an incident: this is due to other process steps

(including writing reports) that are not affected/improved by these controls.

Figure 9-32 shows the specific impact that the new controls have on the time spent in TP iterations,

for all the above three cases:

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Case3

Time to Remediate Major Security Incidents

Days


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Figure 9-32. Comparative Analysis: Time Spent in TP Iterations

The results directly reflect the assumptions made in this what-if scenario. The improvement is

evident. The deployed controls increasingly reduce the overall time spent in TP interactions, from the

current [5,120] days to [1,8] days, in Case 3.

Finally, Figure 9-33 shows the specific impact that the new controls have on the time spent to arrive

to the decision of dealing with risk management, for all the above three cases:

Figure 9-33. Comparative Analysis: Time to Risk Management

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Page 75 of 80

The results show the neat improvement of the time required to deal with the risk management steps in

the process: this is a direct consequence of the improvement of the time required to interact with TPs.

Case 3 shows that this improvement is of an order of magnitude compared to the current situation.

9.2.1.1 Summary

The results shown in Figures 9-31, 9-32 and 9-33 are intuitive and predictable, given the simplicity of

this process and the direct impact that the various parameters have on the outcomes.

The assumptions made in this what-if scenario are coarse grained, as it was not possible to gather

more details about the actual implication and impact that the control and solutions have on the internal

TP processes and their operational activities.

However, these analytic results can be used as a starting point to engage with TPs, in order to explore

options for performance improvement as well as to further reduce ServiceBizWorld’s risk exposures

related to major security incidents.

The Security Analytics model, used in this what-if analysis, can be further refined to accommodate

additional details, information and constraints when available from TPs.


Page 76 of 80

10 Conclusion

The findings of the study suggest that there is major room for improvement for risk reduction and

increase of performance for the analysed processes.

The analysis confirms that TP interactions are a major bottleneck both in the Event/Alert Processing

& Resolution Process and for the Security Incident Management Process. Two key aspects have been

identified as root causes: the lack of SLAs with TPs about how information should be provided to teh

SOC Team; the lack of information availability for TPs.

The what-if scenarios explored using the model of the Event/Alert Processing & Remediation Process

show that:

The definition of SLAs for TPs (e.g. about response time and number of iterations with the SOC

team) can dramatically improve the overall performance and reduce the risk exposure by at least

an order of magnitude;

The current process might expose ServiceBizWorld to additional risks - in terms of delays to

identify security incidents and saturation of TP resources/personnel - if the daily number of new

events to be processed increases by about 30%;

Investments in new controls not only can improve the overall TP information availability and

performance (estimated to be an order of magnitude) but also help to cope with worsening threat

landscapes. Specifically, the adoption of information request templates and manual scripts can

ensure process resilience to a 60% increase of the daily number of new events/alerts to be

processed. The introduction of automation of scripts and/or workflows enables process resilience

to an increase of 90% (or more) of events/alerts.

Similarly, what-if scenarios for the Security Incident Management Process shows that major

improvements can be obtained (for the overall time spent in TP interactions and for the time required

by TPs to remediate to incidents) when templates and incident management support tools are

deployed.

These findings depend on the assumptions made and the information available at the analysis time.

However they provide a starting point for conversations between ServiceBizWorld, TPs and the SOC

Team, on expectations, policy & SLA changes, as well as on potential new investments, to improve

the current process performances, reduce risk exposure and deal with contingency planning for

worsening threat environments.


Page 77 of 80

11 References

[1] ITIL, Incident and Incident Management, http://www.itil-officialsite.com/, 2011

[2] Homeland Security, Build Security In, Incident Management, https://buildsecurityin.us-

cert.gov/bsi/articles/best-practices/incident.html, 2011

[3] HP ArcSight, SIEM solution, http://www.arcsight.com/, 2011

[4] RSA enVision, SIEM solution, http://www.rsa.com/node.aspx?id=3170, 2011

[5] Renaud Bidou, Security Operation Center (SOC) Concepts & Implementation, http://www.iv2-

technologies.com/SOCConceptAndImplementation.pdf

[6] CERT, Computer Security Incident Response Team (CSIRT),

http://www.cert.org/csirts/csirt_faq.html, 2008

[7] MetricStream, Collaborative Incident Analysis and Remediaiton Solutions,

http://www.metricstream.com/solutions/it_incident_management.htm, 2011

[8] WolfPack, Incident Response Plan & Management,

http://www.wolfpacsolutions.com/solutions/incident_response_plan, 2011

[9] BMC Remedy, Change Management, http://www.bmc.com/products/offering/itil-change-

configuration-release-management-software.html

[10] HP Security Analytics, http://h20195.www2.hp.com/V2/GetPDF.aspx/4AA3-2046EEW.pdf,

2011

http://www.itil-officialsite.com/

https://buildsecurityin.us-cert.gov/bsi/articles/best-practices/incident.html

https://buildsecurityin.us-cert.gov/bsi/articles/best-practices/incident.html

http://www.arcsight.com/

http://www.rsa.com/node.aspx?id=3170

http://www.iv2-technologies.com/SOCConceptAndImplementation.pdf

http://www.iv2-technologies.com/SOCConceptAndImplementation.pdf

http://www.cert.org/csirts/csirt_faq.html

http://www.metricstream.com/solutions/it_incident_management.htm

http://www.wolfpacsolutions.com/solutions/incident_response_plan

http://www.bmc.com/products/offering/itil-change-configuration-release-management-software.html

http://www.bmc.com/products/offering/itil-change-configuration-release-management-software.html

http://h20195.www2.hp.com/V2/GetPDF.aspx/4AA3-2046EEW.pdf


Page 78 of 80

A.1 List of parameters - Model 1: Events/Alerts Processing and

Resolution

Parameter Name Type of Parameter Value

Events/Alerts

1 SOC Events and Alerts Frequency 25 events/alerts every day

2 Notification of IT Security Alerts/Events from Third Parties (TP) Frequency 15 events/alerts every day

Triage: Initial Assessment Phase

3 SOC Team: Initial Analysis of the Event/Alert Activity Duration between 1 hour and 2 days

4 Known security problem? Probability/Likelihood 10%

5 --Threat Level Changed? Probability/Likelihood 5%

6 Immediate need to Brief Risk Management Team? Probability/Likelihood 15%

7 -- Prepare Briefing, Brief Team, Agree Remediation Activity Duration between 5 hours and 1 day

8 -- Incident Category Established? Probability/Likelihood 80%

Probability of Major Security Incident: 10%

9 Input required from TP? Probability/Likelihood 80%

10 SOC Investigation (case where TP Input not required) Activity Duration between 1 hour and 2 days

Information Gathering Phase

11 Request Input from TP Activity Duration between 0.5 and 2 hours

12 Agree Timescale for Response Activity Duration between 1 and 5 hours

13 TP responds within defined timeframe? (aggregated over the set of iterations with TP) Probability/Likelihood 60%

14 -- Failure to respond within the defined timeframe Activity Duration between 1 days and 10 days

15 -- Escalate to Risk Management Team? Probability/Likelihood 10%

16 -- Escalation Process

between 1 hour and 3 hours

17 Data provided to SOC Team Activity Duration

First Iteration: between 1 and 10

days

Follow up iterations: between 1

and 3 days

18 SOC Team Investigation Activity Duration between 1 hour and 2 days

19 Brief Risk Management Team? Probability/Likelihood 20%

20 -- Risk Management Team Briefing Activity Duration between 1 and 3 hours

21 Recommended Level Category Activity Duration between 1 and 2 hours

22 Input of acceptable Quality and Quantity? Probability/Likelihood 70%

23 SOC Team Investigation Activity Duration between 1 hour and 1 day

24 Brief Risk Management Team? Probability/Likelihood 10%

25 -- Risk Management Team Briefing Activity Duration between 3 hours and 1 day


Page 79 of 80

26 -- Incident Category Established? Probability/Likelihood 80%


27 Additional Information Required from TP? Probability/Likelihood 90%

5-7 iterations with TP (average: 6)

SOC Team Final Assessment

28 SOC Team Final Analysis Activity Duration between 4 hours and 2 days

29 SOC Team Handling Recommendations Activity Duration between 1 and 5 days

30 Recommended level Category Activity Duration between 2 and 4 hours

31 False Positive? Probability/Likelihood 20%

32 Security Incident? Probability/Likelihood 80%

33 -- Raise Security Incident? Probability/Likelihood 95%


Event Closure

34 Event Closure Activity Duration between 1 and 2 hours

35 Report to Risk Management Team Activity Duration between 1 hour and 1 day

Security Incident

36 Major Security Incident? Probability/Likelihood see various probabilities for Major Security Incidents, above

37 Raising Major Security Incident Activity Duration between 1 and 2 hours

38 Recording of Major Incident Activity Duration between 0.5 and 1 hour

39 Produce Incident Report Activity Duration between 2 and 5 days

40 Raising Minor Security Incident Activity Duration between 0.5 and 1 hour

41 Recording of Minor Incident Activity Duration between 0.5 and 1 hour

42 Produce Minor Incident Report Activity Duration between 1 and 5 hours

TP Non Compliance

43 Raise TP non Compliance Activity Duration between 1 and 2 hours

44 Reporting to Risk Management TEam Activity Duration between 1 and 5 hours

Handling False Positives and Known Problems

45 Known Security Problem with Acceptable Risk? Probability/Likelihood 20%

46 Alert Closure Activity Duration between 0.5 and 1 hours


Page 80 of 80

A.2 List of parameters - Model 2: Incident Management Process

Parameter Name Type of Parameter Value

Major Incident Notification

1 Notification of Major IT Security Incident Frequency

3 events/alerts every day (800-900 Major Incidents per year)

Incident Assessment Phase

2 Exchange of available information between SOC Team and Risk Management Team Activity Duration between 1 hour and 1 day

3 Analysis of the Incident Activity Duration between 1 hour and 1 day

4 Write Summary Report Activity Duration between 1 and 4 hours

Information Gathering from Risk Management Team

5 Additional Information Required from Risk Management Team? Probability/Likelihood 70%

6 -- Request Additional information Activity Duration between 1 and 4 hours

7 -- Wait for Information Activity Duration between 1 and 8 hours

8 -- Additional Joint Analysis Activity Duration between 1 hour and 1 day

9 Agreement on the need for Remediation Requirements Activity Duration between 1 hour and 2 hours

TP Handling of Incident Response

10 Providing Recommendations to TP Activity Duration between 1 hour and 2 days

11 TP Production of Remediation Documents Activity Duration between 5 days and 40 days

12 SOC Team: Analysis of Outcomes and Mitigations Activity Duration between 4 hours and 2 days

13 Satisfactory Response from TP? Probability/Likelihood 45%

NOTE: about 1-3 TP iterations

14 - Make additional requests to TP Activity Duration between 1 and 4 hours

15 Raise Risk? Probability/Likelihood 10%


16 Incident Report Activity Duration between 2 days and 3 days

17 TP Remediation Activity Duration between 5 days and 40 days

Risk Management

18 Incident Report Activity Duration between 2 days and 5 days

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