1. Master Thesis Project Title: Applying Keystroke Dynamics for Personal Authentication By: George Kofi Gagbla

2. Contents • Thesis objectives • Definition, features and characteristics of Biometric systems • Type of biometric systems • Components of Biometric Systems • System Design and implementation • System evaluation and analysis • Conclusion • Demonstration

3. Thesis objectives • Securing E-Business Applications Using Keystroke Dynamics as a Biometric Authentication Technique

4. Definition, features and characteristics of Biometric systems • What is Biometrics ? • User Authentication types • Something you know – a password, PIN or piece of personal information (such as your mother’s maiden name • Something you have – a card key, smart card or a token( like a secured card) • Something you are – a biometric

5. Definition, features and characteristics of Biometric systems ( cont…) • Biometrics measure individuals’ unique physical or behavioral characteristic to recognize or authenticate their identities. • Physiological characteristic: fingerprints, hand or palm geometry, retina, iris or facial characteristics. • Behavioural characteristic: signature, voice (has physical components), keystroke dynamics and gait.

6. Definition, features and characteristics of Biometric systems ( cont…) Features of a Biometric System • Universality • Uniqueness • Permanence • Collectability • Performance • Acceptability • Circumvention

7. Biometric systems Description of Biometric Technologies • Fingerprints • Hand geometry • Face recognition • Voice recognition • Retina scanning • Iris scanning • Hand Signature • Keystroke dynamics • Multimodal Biometric systems

8. System Design and Implementation System Development • Web client • Web server • Database Server • Off-line simulator • Survey modular system

9. System Design and Implementation Feature characteristics • Key codes ( BreAkfaSt) • Key Press-Press • Key Press-Release • Key Release-Release • Key Release-Press

10. System Design and Implementation

11. System evaluation and analysis Login user classification • Legitimate user • Impostor user • Observer impostor

12. System evaluation and analysis Decision error rates • False Accept Rate (FAR) • False Reject Rate (FRR) • Equal Error Rate (EER)

13. System evaluation and analysis (cont...)

14. System evaluation and analysis (cont...)

15. System evaluation and analysis (cont...) FAR and FRR plot for verification one based on 5 keystroke features and 20 template samples

16. System evaluation and analysis (cont...) FAR and FRR plot for verification one based on 1 keystroke feature and 20 template samples

17. System evaluation and analysis (cont...) FAR and FRR (%) FAR and FRR for verification two based on 5 template samples and 5 keystroke features

18. System evaluation and analysis (cont...) FAR and FRR (%) FAR and FRR for verification two based on 10 template samples and 5 keystroke features

19. System evaluation and analysis (cont...) Type I : A!teche197 Type II : www.google.com Effect of target password string familiarization

20. Conclusion • Effects of number of keystroke features and template samples on the results were analyzed • Acceptable levels of FAR and FRR were achieved • Future improvements (the choice of keyboard): • Designing an automatic recognition tool to match templates based on choice of keyboard to increase system mobility.

21. Thanks for the audience… Questions???