By Topic

RACOON: rapidly generating user command data for anomaly detection from customizable template

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.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Ramkumar Chinchani ; State Univ. of New York, Buffalo, NY, USA ; Muthukrishnan, A. ; Chandrasekaran, M. ; Upadhyaya, S.

One of the biggest obstacles faced by user command based anomaly detection techniques is the paucity of data. Gathering command data is a slow process often spanning months or years. In this paper, we propose an approach for data generation based on customizable templates, where each template represents a particular user profile. These templates can either be user-defined or created from known data sets. We have developed an automated tool called RACOON, which rapidly generates large amounts of user command data from a given template. We demonstrate that our technique can produce realistic data by showing that it passes several statistical similarity tests with real data. Our approach offers significant advantages over passive data collection in terms of being nonintrusive and enabling rapid generation of site-specific data. Finally, we report the benchmark results of some well-known algorithms against an original data set and a generated data set.

Published in:

Computer Security Applications Conference, 2004. 20th Annual

Date of Conference:

6-10 Dec. 2004