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IT 691 Capstone Project

IT 691 Capstone Project. Keystroke Biometric System. Client: Dr. Mary Villani (SUNY Farmingdale) Instructor: Dr. Charles Tappert. Team 4: Tarjani Buch Andreea Cotoranu Eric Jeskey Florin Tihon. Introduction.

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IT 691 Capstone Project

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  1. IT 691 Capstone Project Keystroke Biometric System Client: Dr. Mary Villani (SUNY Farmingdale) Instructor: Dr. Charles Tappert Team 4: Tarjani Buch Andreea Cotoranu Eric Jeskey Florin Tihon

  2. Introduction • Keystroke biometric systems measure typing characteristics believed to be unique to an individual and difficult to duplicate; • A keystroke biometric identification system was developed in the Seidenberg School in 2004 and has since gone through four project iterations with different graduate student teams; • The system identifies subjects based on long-text (about 650 keystrokes) samples;

  3. Project Requirements • Enhance the feature extractor component of the system to output feature data in a standard format; • Implement new data collection schedule and collect new data samples to support a longitudinal study on identification experiments; • Rerun some of the previous experiments with new data samples; • Deliver feature data to back-end teams for additional identification and authentication experiments; • Update project web site

  4. System Specifications • Pace University’s Utopia Server • FTP client • Java IDE (Borland’s JBuilder recommended) • Java JDK (latest version)

  5. System Components • The keystroke biometric system consists of three main components: • Java applet for collection of raw data • Feature extractor • Pattern classifier

  6. System Components (Contd.) • Java Applet for collection of raw data • Subjects need to register in order to participate in the data collection process; • There are four data entry tasks: • Copy task on a Desktop • Copy task on a Laptop • Free text entry on a Desktop • Free text entry on a Laptop

  7. System Components (Contd.) • Java Applet

  8. System Components (Contd.) • Feature Extractor

  9. System Components (Contd.) • Pattern Classifier

  10. New Feature Data Output

  11. New Data Collection Schedule

  12. Summary of Experimental Design 1 4 3 6 5 2

  13. Previous Identification Experiments

  14. New Identification Experiments

  15. New Identification Experiments (Contd.)

  16. Summary • New experiments support previously documented accuracy findings; • New experiments show that a high level of accuracy can be maintained over time; • All experimental results are promising in that the system has the capability of solving identification problems and the potential for solving authentication problems;

  17. Future Recommendations • Running experiments with a larger data pool collected under the discussed conditions should provide stronger evidence relative to the success of the keystroke biometric system for identifying and eventually for authenticating subjects. It would also provide more insight into how accuracy evolves from one data collection session to another over time.

  18. Communication • A single face-to-face meeting with Dr. Mary Villani to get an understanding of the previous work and explore the potential for future developments • Bi-weekly group meetings on IM • Email communication with the stakeholders on a need basis • Team Roles: Tarjani Buch – Data Collection Coordinator Andreea Cotoranu – Team Coordinator - Liaison Eric Jeskey – Architect / Designer Florin Tihon – Quality Officer / Tester

  19. Deliverables/Accomplishments • Technical Paper • User Manual • Enhanced Feature Extractor program to output feature vector in a standard format including normalization of feature values into the range 0-1 • Raw data collection with team members as test subjects at two-week intervals • Interval 1: T0 - November 3rd 2007 • Interval 2: T1 - November 17th 2007 • Interval 3: T2 - December 3rd 2007

  20. Keystroke Biometric SystemThank You http://utopia.csis.pace.edu/cs691/2007-2008/team4/

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