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Computer-User-Input Behavioral Biometrics The Biometrics we focus on at Pace University Dr. Charles C. Tappert Seidenberg School of CSIS, Pace University.

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Presentation on theme: "Computer-User-Input Behavioral Biometrics The Biometrics we focus on at Pace University Dr. Charles C. Tappert Seidenberg School of CSIS, Pace University."— Presentation transcript:

1 Computer-User-Input Behavioral Biometrics The Biometrics we focus on at Pace University Dr. Charles C. Tappert Seidenberg School of CSIS, Pace University Subtitle GenCyber Cybersecurity Workshop at Pace University

2 Importance of Computer-Input Biometrics to Identify or Authenticate Computer Users
DARPA: Active Authentication – DoD wants to continually authenticate all gov’t computer users Phase 1: 2010 and 2012 – authenticate users on desktops/laptops Phase 2: 2013 and 2015 – authenticate users on mobile devices DARPA: Enhanced Attribution – DoD wants technology to attribute actions in cyberspace to individuals – network behavior and activity tracking of individuals, fusing generated data for predictive analysis

3 Importance of Computer-Input Biometrics to Identify or Authenticate Computer Users
U.S. Higher Education Opportunity Act of 2008 Concerns authentication of students taking online tests Universities are using more online courses Requires institutions of higher learning to adopt new identification technologies as they become available To assure students of record are those accessing the systems and taking the exams in online courses

4 Attribution and Intrusion Detection Plan Multi-biometric System
Motor control level – keystroke + mouse movement Linguistic level – stylometry (char, word, syntax) Semantic level – target likely intruder commands Intruder Keystroke + Mouse Stylometry Motor Control Level Linguistic Semantic

5 Keystroke Biometrics Based on idea that generated patterns are unique to individuals and difficult to duplicate Appeal of keystroke over other biometrics Not intrusive, inexpensive, continual user verification The keystroke biometric is one of the less-studied behavioral biometrics

6 Pace Univ. Keystroke Biometric Studies
Most literature studies have been on short input of a few seconds Commercial products on hardening passwords Pace University studies on desktop/laptop mechanical keyboards Short input of few seconds Vinnie Monaco, now at ARL, entered 2016 contest: we have World’s Best System Phone number – similar to CMU study (Ned Bakelman and Vinnie Monaco) Long text input of several minutes Online test taking (Mary Villani, John Stewart, Vinnie Monaco, Steve Kim) Impaired users – left hand, right hand, and both hands input (Gonzalo Perez) Pace University studies on mobile device touchscreens Numeric input – phone # – similar to CMU study (Mike Coakley) Features – pressure & location/area of finger press on keys, acceleration & gyroscope information Names are doctoral students

7 Mouse Movement and Stylometry Traits

8 Pace Univ. Mouse & Stylometry Studies
Combining keystroke/stylometry info: John Stewart Stylometry can compliment keystroke analysis The correct student may be keying in the test answers provided by a coach, with the student merely typing the coach’s words This would not be discovered via keystroke analysis But potentially could through stylometry analysis Stylometry analysis of Facebook postings Dissertation study by Jenny Li

9 Copyright for Material Reuse
This materials are developed under the support of the GenCyber program of the National Security Agency and the CyberCorps program of the National Science Foundation. Copyright© Charles Tappert Pace University. Please properly acknowledge the source for any reuse of the materials as below. Charles Tappert, 2016 GenCyber Cybersecurity Workshop, Pace University Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.3 or any later version published by the Free Software Foundation. A copy of the license is available at

10 Acknowledgment The authors would like to acknowledge the support from the GenCyber program of the National Security Agency and the CyberCorps program of the National Science Foundation. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation, the National Security Agency or the U.S. government.


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