The insider threat is one of the most difficult problems in information security. Prior research addresses its detection by using machine learning techniques to profile user behavior. User behavior is represented as low level system events, which do not provide sufficient contextual information about the user's intentions, and lead to high error rates. Our system uses video of a user's sessions as the representation of their behavior, and detects moments during which they perform sensitive tasks. Analysis of the video is accomplished using OCR, scene detection algorithms, and basic text classification. The system outputs the results to a web interface, and our results show that using desktop imagery is a viable alternative to using system calls for insider threat detection.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Luli, Klevis
• Muchene, David N.

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-121812-135836

Advisor

• Shue, Craig A.

Year

• 2012

Date created

• 2012-12-18

Resource type

• Major Qualifying Project

Major

• Computer Science

Rights statement

• In Copyright