TEAMS 2 & 4 THE MICHAEL L. GARGANO 9TH ANNUAL RESEARCH DAY PRESENTATION PRESENTERS EDYTA ZYCH & VINNIE MONACO May 6, 2011 Seidenberg School of Computer Science and Information Systems Pace University, Graduate Center White Plains, New York Keystroke Biometric & Stylometry Systems
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T EAMS 2 & 4 R ESEARCH D AY P RESENTATION P RESENTERS T EAMS 2 & 4 T HE M ICHAEL L. G ARGANO 9 TH A NNUAL R ESEARCH D AY P RESENTATION P RESENTERS E DYTA.
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TEAMS 2 & 4THE MICHAEL L. GARGANO 9TH ANNUAL
RESEARCH DAY PRESENTATION
PRESENTERSEDYTA ZYCH & VINNIE MONACO
May 6, 2011Seidenberg School of Computer Science and Information Systems
Pace University, Graduate Center
White Plains, New York
Keystroke Biometric& Stylometry Systems
AGENDA
Team and Project Leader Introductions
KBS & Stylometry Projects Overview
Project Specifications & Deliverables
System Components & Enhancements
Results & Conclusions
Future Work
PROJECT STAKEHOLDERS
Team Members Vinnie Monaco Tyrone Allman Mino Lamrabat Mandar Manohar
Customers / SMEs Dr. Tappert John Stewart Robert Zack
Team Members Edyta Zych Omar Canales Vinnie Monaco Thomas Murphy
Customers / SMEs Dr. Tappert John Stewart
Keystroke Biometric
Stylometry
TWO PROJECTS ACT AS ONE, TWO TEAM LEADS
Person ManagerFacilitate Weekly Meeting ScheduleTask AssignmentsDriving Everyday ActivitiesTech Training & Documentation
Technical ManagerSubject Matter Expert (SME)Technical ScopeDesign & Implementation of all System
EnhancementsProgramming Tasks
OVERVIEW: KEYSTROKE BIOMETRIC SYSTEM
Pace University has conducted over 8 years of research on Keystroke Biometrics
The Keystroke Biometric System (KBS) can be used for both identifying and authenticating users from their typing rhythms
Keystroke dynamics are the patterns of rhythm and timing created when a person types, including: Overall speed Variations of speed moving between specific keys Common errors The length of time that keys are depressed (duration)
This semester’s work focuses solely on the KBS as it relaters to an online test taking environment
OVERVIEW: STYLOMETRY
Stylometry is the study of the unique linguistic styles and writing behaviors of individuals in order to determine authorship
Stylometry uses statistical pattern recognition, and artificial intelligence techniques
Stylometry features typically used to analyze text include word frequencies and identifying patterns in common parts of speech
This semester’s work focuses on text input being used in conjunction with the keystroke analysis to improve authentication results including Determining authorship in documents (Beneficial
academically to assist with on-line test taking) Protecting against plagiarism through a third party
PROJECT SPECIFICATIONS
Work closely with our project customer to define the most appropriate Keystroke & Stylometry Features and add additional features to assist in validating/authenticating the identity of students taking an online exam
Extract the selected Feature Set for Keystroke Biometric and Stylometry Analysis and run experiments to measure program performance utilizing the enhanced systems: Input System, Feature Extractor and Classifier
Run experiments and tests on the data collected to support the identification of subject and online test-taker authorship