Cart (Loading....) | Create Account
Close category search window
 

Use of Domain Knowledge to Detect Insider Threats in Computer Activities

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

The purchase and pricing options are temporarily unavailable. Please try again later.
5 Author(s)

This paper reports the first set of results from a comprehensive set of experiments to detect realistic insider threat instances in a real corporate database of computer usage activity. It focuses on the application of domain knowledge to provide starting points for further analysis. Domain knowledge is applied (1) to select appropriate features for use by structural anomaly detection algorithms, (2) to identify features indicative of activity known to be associated with insider threat, and (3) to model known or suspected instances of insider threat scenarios. We also introduce a visual language for specifying anomalies across different types of data, entities, baseline populations, and temporal ranges. Preliminary results of our experiments on two months of live data suggest that these methods are promising, with several experiments providing area under the curve scores close to 1.0 and lifts ranging from ×20 to ×30 over random.

Published in:

Security and Privacy Workshops (SPW), 2013 IEEE

Date of Conference:

23-24 May 2013

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.