On the Evolution of Adversary Models (from the beginning to sensor networks)

VDG, July 17, 2007 1 Copyright © 2007

On the Evolution of Adversary Models(from the beginning to sensor networks)

Virgil D. Gligor Electrical and Computer Engineering

University of MarylandCollege Park, MD. 20742

[email protected]

Lisbon, PortugalJuly 17-18, 2007


Overview

1. New Technologies often require a New Adversary Def.- continuous state of vulnerability

2. Why is the New Adversary Different ? - ex. sensor, mesh networks, MANETs

- countermeasures

3. Challenge: find “good enough” security countermeasures

4. Proposal: Information Assurance Institute


A system without an adversary definition cannotpossibly be insecure; it can only be astonishing…

… astonishment is a much underrated security vice.(Principle of Least Astonishment)


1. New Technology > Vulnerability ~> Adversary <~> Methods & Tools

Why an Adv. Def. is a fundamental concern ?

-sharing user-mode confidentiality and untrusted user- sys. vs. user mode (’62->) programs& data; integrity breaches; mode programs rings, sec. kernel (’65, ‘72)- computing utility system penetration; & subsystems FHM (’75) theory/tool (’91)*(early – mid 1960s) acc. policy models (’71)

- shared stateful DoS instances untrusted user DoS = a diff. prob.(83-’85)*services processes; formal spec. & verif. (’88)*

e.g., DBMS, net. protocols concurrent, DoS models (’92 -> ) dyn. resource alloc. coord. attacks(early - mid 1970s)

- PCs, LANs; read, modify, block, “man in the middle” informal: NS, DS (’78–81)public-domain Crypto replay, forge active, adaptive semi-formal: DY (‘83)(mid 1970s) messages network adversary Byzantine (‘82 –>)

crypto attk models (‘84->) auth. prot. analysis (87->)

- internetworking large-scale effects: geo. distributed, virus scans, tracebacks (mid – late 1980s) worms, viruses, coordinated intrusion detection

DDoS (e.g., flooding) attacks (mid ’90s ->)

2. Technology Cost -> 0, Security Concerns persist


Continuous State of Vulnerability

New Technology >

New Vulnerability ~>

New Adversary Model <~>

New AnalysisMethod & Tools

+/- O(months) +O(years)

+O(years)

Reuse of Old (Secure)Systems & Protocols

New Technology ~>

New Vulnerability

OldAdversary Model

… a perennial challenge (“fighting old wars”)

mismatch


New Technology Ex.: Sensor Networks

Claim

Sensor Networks introduce:

- new, unique vulnerabilities: nodes captured and replicated

- new adversary: different from and Dolev-Yao and traditional Byzantine adv.s

and

- require new methods and tools: emergent algorithms & properties (for imperfect but good-enough security)

Mesh Networks have similar but not identical characteristics


Two Extreme Examples

Low end: Smart Cards (< $15) High end: IBM 4764 co-proc. (~ $9K)

- no tamper resistance- non-invasive phys. attacks

- side-channel (timing, DPA)- unusual operating conditions

- temperature, power clock glitches

- invasive phys. attacks- chip removal from plastic cover- microprobes, electron beams

- tamper resistance, real time response- independent battery, secure clock- battery-backed RAM (BBRAM)- wrapping: several layers of non-metallic grid of conductors in a grounded shield to reduce detectable EM emanations- tamper detection sensors (+ battery)

- temp., humidity, pressure, voltage, clock, ionizing radiation

- response: erase BBRAM, reset device

Limited Physical Node Protection


Observation: a single on-chip secret key is sufficient to protect (e.g., via Authenticated Encryption) many other memory-stored secrets (e.g., node keys)

Problem: how do we protect that single on-chip secret key ?

Potential Solution: Physically Unclonable Functions (PUFs)

observation: each IC has unique timing

basic PUF: Challenge extracts unique, secret Response (i.e., secret key) from

IC-hidden, unique timing sequence

Limited Physical Node Protection


b0 b1 b2 b61 b128

bi=0 bi=1

Arbiter

switch

01

Arbiter 0

Arbiter 1

Arbiter operation

LFSR Challengee.g., 128 bits

Responsee.g., 255 bits

Basic PUF circuit [Jae W. Lee et al. VLSI ‘04]

b62feed-fwd arbiter

unknown challenge bit

IC

255


Basic PUF counters:

brute-force attacks (2*128 challenge-response pairs => impractical)

duplication (different timing => different Secret Response)

invasive attacks (timing modification => different Secret Response)

However,

Pr. 1: adversary can build timing model of Arbiter’s output=> can build clone for secret-key generation

Pr. 2: Arbiter’ output (i.e., secret-key generation) is unreliableReality: intra-chip timing variation (e.g., temp, pressure, voltage)

=> errors in Arbiter’s output (e.g., max. error: 4 – 9%)

Basic PUF circuit [Jae W. Lee et al. VLSI ‘04]


Suggested PUF circuit [Ed Suh et al. ISCA ‘05]

Solution to Pr. 1: hash Arbiter’s output to provide new Response - cannot discover Arbiter output from known Challenges and new Responses

Solution to Pr. 2: add Error Correcting Codes (ECCs) on Arbiter’s output

e.g., use BCH(n, k, d) n(timing bits) = k(secret bits) + b(syndrome bits) for (d-1)/2 errors

BCH (255,63,61) => 30 (> 10%n > max. no.) errors in Arbiter’s output are corrected > 30 errors ? (probability is 2.4 X10-6)

probability of incorrect output is smaller but not zero

hash Arbiter’s output and verify against stored Hash(Response)


Suggested PUF circuit

b0 b1 b2 b61 b128

Arbiter

LFSRknownChallengee.g., 128 bit

secretResponse

b62feed-fwd arbiterBCH

knownSyndromee.g., 192 bits

Hash

(Off-line) Verifiable-Plaintext Attack:Get C, S, hash(R); guess remaining (e.g., 63) bits of Arbiter’s output; verify new R; repeat verifiable guesses until Arbiter’s output is known; discover secret key

However, syndrome reveals some (e.g., b=192) bits of Arbiter’s output (n=255)

IC

255bits

generate response: C -> R, S; retrieve response: C, S -> R


Some Characteristics of Sensor Networks

1. Ease of Network Deployment and Extension- scalability => simply drop sensors at desired locations- key connectivity via key pre-distribution =>

neither administrative intervention nor TTP interaction

2. Low Cost, Commodity Hardware - low cost => physical node shielding is impractical

=> ease of access to internal node state(Q: how good should physical node shielding be to prevent access to a sensor’s internal state ?)

3. Unattended Node Operation in Hostile Areas => adversary can capture, replicate nodes (and node states)


NEIGHBORHOOD i

1

3i

2

Captured Node

3

Replicated Node Insertion: How Easy ?

shared keyoutside neighborhood

shared keyoutside neighborhood

NEIGHBORHOOD j

NEIGHBORHOOD k

shared key

inside neighborhood

path key


NEIGHBORHOOD j

NEIGHBORHOOD i

1

3i

2

Captured Node

3

NEIGHBORHOOD k

3

Node

Replica 1

3

Node

Replica 2

Note: Replica IDs are cryptographically bound to pre-distributed keys and cannot be changed

Attack Coordination among Replicas: How Easy ?

collusion


New vs. Old Adversary

Old Byzantine Adversaries - can do 1) but not 2) - consensus problems impose fixed thresholds for captured nodes

(e.g., t < n/2, t < n/3) and fixed number of nodes, n.

Old (Dolev-Yao) Adversary can - control network operation

- man-in-the-middle: read, replay, forge, block, modify, insert messages anywhere in the network

- send/receive any message to/from any legitimate principal (e.g., node) - act as a legitimate principal of the network

Old (Dolev-Yao) Adversary cannot 1) adaptively capture legitimate principals’ nodes and discover a legitimate principal’s secrets 2) adaptively modify network and trust topology (e.g., by node replication)


Countermeasures for Handling New Adv.?

1. Detection and Recovery - Ex. Detection of node-replica attacks- Cost ? Traditional vs. Emergent Protocols - Advantage: always possible, good enough detection- Disadvantage: damage possible before detection

2. Avoidance: early detection of adversary’s presence- Ex. Periodic monitoring - Cost vs. timely detection ? False negatives/positives ?- Advantage: avoids damage done by new adversary- Disadvantage: not always practical in MANETs, sensor and mesh networks

3. Prevention: survive attacks by “privileged insiders”- Ex. Subsystems that survive administrators’ attacks (e.g., auth)- Cost vs. design credibility ? Manifest correctness

- Advantage: prevent damage; Disadvantage: very limited use


Example of Detection and Recovery

(IEEE S&P, May 2005)

- naïve: each node broadcasts <ID, “locator,” signature> perfect replica detection: ID collisions, different Iocators complexity: O(n2) messages

- realistic: each node broadcasts locally <ID, “locator,” signature> local neighbors further broadcast to g << n random witnesses good enough replica detection: ID collision, different

Iocators at witness detection probability: 70 - 80% is good enough

complexity: O(n x sqrt(n)) messages


A New App.: Distributed Sensing


A New Application: Distributed Sensing

Application: a set of m sensors observe and signal an event - each sensor broadcasts “1” whenever it senses the event;

else, it does nothing - if t m broadcasts, all m sensors signal event to neighbors; else do nothing

New (Distributed-Sensing) Adversary - captures nodes, forges, replays or suppresses (jams) broadcasts

(within same or across different sessions) - increases broadcast count with outsiders’ false broadcasts

Operational Constraints - absence of event cannot be sensed (e.g., no periodic “0” broadcasts) - broadcasts are reliable and synchronous (i.e., counted in sessions)

Adversary Goals: violate integrity (i.e., issues t m/2 false broadcasts) deny service (i.e., t > m/2, suppresses m-t+1 broadcasts)


32

1

8

9

104

5

6

7

CommunicationNeighborhood

revocation target

An Example: distributed revocation decision[IEEE TDSC, Sept. 2005]

11

12

13

14

m=6, t = 4 votes in a session => revoke target

propagate revocation

decision

propagate re

voca

tion

decision

Keying Neighborhood


New vs. Old Adversary

A (Reactive) Byzantine Agreement Problem ? - both global event and its absence are (“1/0”) broadcast by each node - strong constraint on t ; i.e., no PKI => t > 2/3m; PKI => t >m/2 - fixed, known group membership

New (Distributed-Sensing) Adv. =/= Old (Byzantine) Adv. - new adversary need not forge, initiate, or replay “0” broadcasts - new adversary’s strength depends on a weaker t (e.g., t < m/2) - new adversary may modify membership to increase broadcast count ( > t)

No.


Conclusions

3. How effective are the countermeasures ?- provide “good enough” security; e.g., probabilistic security

properties

1. New Technologies => New Adversary Definitions- avoid “fighting the last war”- security is a fundamental concern of IT

2. No single method of countering new and powerful adversaries- detection- avoidance (current focus) - prevention (future)

Documents

On the Evolution of Adversary Models (from the beginning to sensor networks)