1. Keystroke Biometric Studies Security Research at Pace Keystroke Biometric Drs. Charles Tappert and Allen Stix Seidenberg School of CSIS

2. Keystroke Biometric Studies Introduction Validate importance of study – applications Internet authentication application Authenticate (verify) student test-takers Internet identification application Identify perpetrators of inappropriate email Internet security for other applications Important as more businesses move toward e-commerce

3. Keystroke Biometric Studies Introduction Define Keystroke Biometric The keystroke biometric is one of the less-studied behavioral biometrics Based on the idea that typing patterns are unique to individuals and difficult to duplicate

4. Keystroke Biometric Studies Introduction Appeal of Keystroke Biometric Not intrusive – data captured as users type Users type frequently for business/pleasure Inexpensive – keyboards are common No special equipment necessary Can continue to check ID with keystrokes after initial authentication As users continue to type

5. Keystroke Biometric Studies Introduction Previous Work on Keystroke Biometric One early study goes back to typewriter input Identification versus authentication Most studies were on authentication Two commercial products on hardening passwords Few on identification (more difficult problem) Short versus long text input Most studies used short input – passwords, names Few used long text input –copy or free text Other keystroke problems studies One study detected fatigue, stress, etc. Another detected ID change via monitoring

6. Keystroke Biometric Studies Introduction Feature Measurements Features derived from raw data Key press times and key release times Each keystroke provides small amount of data Data varies from different keyboards, different conditions, and different entered texts Using long text input allows Use of good (statistical) feature measurements Generalization over keyboards, conditions, etc.

7. Keystroke Biometric Studies Introduction Make Case for Using Data over the internet Required by applications Long text input More and better features Higher accuracy Free text input Required by applications Predefined copy texts unacceptable

8. Keystroke Biometric Studies Introduction Summary of Scope and Methodology Determine distinctiveness of keystroke patterns Two application types Identification (1-of-n problem) Authentication (yes/no problem) Two indep. variables (4 data quadrants) Keyboard type – desktop versus laptop Entry mode – copy versus free text

9. Keystroke Biometric Studies Keystroke Biometric System Components Raw keystroke data capture Feature extraction Classification for identification Classification for authentication

10. Keystroke Biometric Studies Keystroke Biometric System Raw Keystroke Data Capture

11. Keystroke Biometric Studies Keystroke Biometric System Raw Keystroke Data Capture

12. Keystroke Biometric Studies Keystroke Biometric System Feature Extraction Mostly statistical features Averages and standard deviations Key press times Transition times between keystroke pairs Individual keys and groups of keys – hierarchy Percentage features Percentage use of non-letter keys Percentage use of mouse clicks Input rates – average time/keystroke

13. Keystroke Biometric Studies Keystroke Biometric System Feature Extraction A two-key sequence (th) showing the two transition measures

14. Keystroke Biometric Studies Keystroke Biometric System Feature Extraction Hierarchy tree for the 39 duration categories

15. Keystroke Biometric Studies Keystroke Biometric System Feature Extraction Hierarchy tree for the 35 transition categories

16. Keystroke Biometric Studies Keystroke Biometric System Feature Extraction Two preprocessing steps Outlier removal Remove duration and transition times > threshold Feature standardization Convert features into the range 0-1

17. Keystroke Biometric Studies Keystroke Biometric System Classification for Identification Nearest neighbor using Euclidean distance Compare a test sample against the training samples, and the author of the nearest training sample is identified as the author of the test sample

18. Keystroke Biometric Studies Experimental Design and Data Collection Design Two independent variables Keyboard type Desktop – all Dell Laptop – 90% Dell + IBM, Compaq, Apple, HP, Toshiba Input mode Copy task – predefined text Free text input – e.g., arbitrary email

19. Keystroke Biometric Studies Experimental Design and Data Collection

20. Keystroke Biometric Studies Experimental Results Identification Experimental Results Identification performance under ideal conditions (same keyboard type and input mode, leave-one-out procedure)

21. Keystroke Biometric Studies Experimental Results System hierarchical model and parameters Identification accuracy versus enrollment samples

22. Keystroke Biometric Studies Experimental Results System hierarchical model and parameters Distributions of “u” duration times for each entry mode

23. Keystroke Biometric Studies Conclusions Results are important and timely as more people become involved in the applications of interest Authenticating online test-takers Identifying senders of inappropriate email High performance (accuracy) results if 2 or more enrollment samples/user Users use same keyboard type