By Topic

An Evaluation of the Effectiveness of Measurement-based Anomaly Detection Techniques

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

2 Author(s)
Seong Soo Kim ; Texas A&M University, College Station, TX, USA ; Reddy, A.L.N.

A number of recent studies have proposed measurement based approaches to network traffic analysis. These techniques treat traffic volume and traffic header data as signals or images in order to make analysis feasible. We use trace-driven experiments and compare the performance of different strategies. Our evaluations on real traces reveal differences in the effectiveness of different traffic header data as potential signals for traffic analysis in terms of their detection rates and false alarm rates. Our results show that address distributions and number of flows are better signals than traffic volume for anomaly detection.

Published in:

Distributed Computing Systems Workshops, 2006. ICDCS Workshops 2006. 26th IEEE International Conference on

Date of Conference:

04-07 July 2006