(2011) Dynamic Signature Verification and The HBSI Model

DYNAMIC SIGNATURE VERIFICATION AND THE HBSI MODELPurdue University: Michael Brockly | Stephen Elliott University of Kent: Richard Guest | James Scott

RESEARCH QUESTION

• How can the Human-Biometric Sensor Interaction (HBSI) Model be further updated for behavioral biometrics?

• Can this be done for behavioral biometrics, especially dynamic signature verification?

CURRENT HBSI MODEL

RESPONSIVE

• Currently the model has been created for physiological biometrics and tested most extensively with fingerprint.

• As behavioral biometrics become more trusted, the HBSI model needs to stay current.

RELEVANT

• Signing as a proof of identity is no new idea• Dynamic Signatures can be a strong anti-theft

device

BEHAVIORAL BIOMETRICS

• Signature, keystroke, voice, mouse movement

• Different from physiological biometrics• Increase in variability

DYNAMIC SIGNATURE VERIFICATION (DSV)

• Use digitizer to capture interaction• Common metrics:

- min/max/avg velocity- in both x and y dimensions

- pen up / pen down time- size of signature- total pen distance- more

2 DIGITIZERS

• Virtual Ink- ePad Ink

• Paper and Ink- ePad

VIRTUAL INK DIGITIZER

VIRTUAL INK FLOWCHART

PAPER AND INK DIGITIZER

PAPER AND INK FLOWCHART

INCORRECT PRESENTATIONS

• Incorrect presentations are errors caused by the signer at point of transaction

• These errors include:- Defective Interactions- Concealed Interactions- False Interactions

DEFECTIVE INTERACTIONS

Signature is deemed incorrect and no signature channel data is collected

• Pen pressure too light at all sample points in paper and ink system

• No virtual ink is presented as feedback to the signer in a virtual ink system

• Latency or temporal error causes data to not be recorded

• User abandons process before data is collected

CONCEALED INTERACTIONS

Signature is deemed incorrect and is not detected by the system

• User not satisfied but does not abandon• Signature not captured due to latency• Signature out of bounds• Pen pressure or ink dispersal incorrect

FALSE INTERACTIONS

Signature is deemed incorrect or unrepresentative by the signer with sample points recorded

• Repetitive motion due to faulty ink flow or varying pressure

• Repetitive motion due to errors by the signer• Incomplete/unrepresentative signature due to

bodily movements• Pen interface issues

CORRECT PRESENTATIONS

• Errors can still occur despite a correct presentation:

- Failure to Detect- Failure to Process

• If no errors occur:- Successfully Processed Sample

FAILURE TO DETECT

Occur when the signer has donated a signature that they have deemed acceptable but is not detected by the biometric system

• Pen pressure is too light across all sample points even though ink (virtual or physical) is left on the surface/digitizer

• No samples are recorded due to latency

FAILURE TO PROCESS

Occur when the signature has been deemed acceptable and detected by the system but not considered as an accurate representation

• Latency or other temporal errors result in partially captured signature

• Start and/or end segments are missing• Part of signature it outside capture area

- Occurs if boundary areas are not defined• Pen pressure is too light across all sample

points even though ink (virtual or physical) is left on the surface/digitizer

FTP CONTINUED

• Pen pressure is variable and too low in some areas although though ink (virtual or physical) is left on the surface/digitizer

• Pen malfunction causes channel data disruption

- Barrel button pressed during donation• System performance fails to capture certain

parts of a signature- Machine with too low of free memory

SUCCESSFULLY PROCESSED SAMPLE (SPS)

This is the result of a correct presentation that both the user and biometric system have deemed correct

RESULTS

• 10 potential error points in both the paper and ink system, as well as the virtual ink system

• Paper and Ink System- Potential for 1 FTD, 3 FTP, 4 FI, 3 CI, and

1 DI• Virtual Ink System

- Potential for 1 FTD, 2 FTP, 6 FI, 6 CI, and 1 DI

REVISED HBSI MODEL

FUTURE WORK

• Data collection to further test this model• Examination of non-genuine users• Test with more behavioral biometrics

- Voice, keystroke, etc.

CONTACT INFORMATION

Michael Brockly• Undergraduate Researcher at BSPA Lab• mbrockly@purdue.edu

Richard Guest PhD• Senior Lecturer at University of Kent• r.m.guest@kent.ac.uk

Stephen Elliott PhD• Associate Professor at BSPA Lab• elliott@purdue.edu

James Scott• Graduate Researcher at University of Kent• jas63@kent.ac.uk