DARPA-BAA Proposal 2012 Active Authentication Technical POC: Dr. Charles Tappert Principal Investigators: Drs. Tappert, Cha, Chen, Grossman

DARPA – Active Authentication DARPA Proposal 2012 Request for Proposal (RFP) c f0276fc1b28817c581d86&tab=core&_cview=0 c f0276fc1b28817c581d86&tab=core&_cview=0 Proposal Due March 6, 2012 Work Duration: 4/1/12 - 3/31/13 Continuations possible Perks – we are applying for 3-4 DPS half tuitions (start with half tuitions per semester) 2 Masters half tuitions

DARPA – Active Authentication Active Authentication Gov’t wants to continually authenticate all users of gov’t desktop computers Objective – detect intruders (unauthorized users) of gov’t machines Continual authentication – ongoing but with possible interruptions in contrast to continuous authentication which would mean without interruption

DARPA – Active Authentication Proposed Technologies Keystroke/Mouse Biometrics Unconscious level: ballistic motor control Stylometry Linguistic level: character, word, syntax Intentional Behavior Semantic level

DARPA – Active Authentication DPS Keystroke Biometric Dissertations 1. Long-text keystroke biometric applications over the Internet Dr. Mary Curtin, Keystroke biometric recognition studies on long text input Dr. Mary Villani, Strategies for managing missing and incomplete information Dr. Mark Ritzmann, An improved kNN classifier with appl to keystroke bio authentication Dr. Robert Zack, An investigation of keystroke and stylometry traits John Stewart (in progress, almost done - manuscript being reviewed) 6. Keystroke biometric intrusion detection Ned Bakelman (in progress)

DARPA – Active Authentication Possible DPS Dissertation Problems (in order of recommended priority) 1. New or improved biometric systems Keystroke/mouse biometric system (motor control level) Stylometry biometric system (char/word/syntax linguistic level) Intruder operational behavior biometric system (semantic level) 2. Dichotomy model – weak versus strong training For large populations we can’t train system on all users 3. Continual training of the biometric systems Continual training – how often?, measure performance Explore methods – e.g., give more weight to recent training data 4. Weak biometrics (mouse, stylometry) assist strong ones (keystroke) Clustering method suggested 5. Evaluate setting ROC-curve operating point for individual users to explicitly control individual risk mitigation