By Topic

Statistical analysis for origin-destination traffic anomalies

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

7 Author(s)
Dingde Jiang ; Coll. of Inf. Sci. & Eng., NEU, Shenyang, China ; Hongwei Xu ; Zhengzheng Xu ; Zhenhua Chen
more authors

Origin-Destination (OD) traffic anomalies reflect network-level traffic anomaly behaviors, which is significantly dangerous to network operation. OD traffic anomalies in a network are investigated in this paper, using statistical analysis based on principle component analysis (PCA). Firstly, we use PCA method to analyze network traffic characteristics and to divide OD flows in the network into both normal and abnormal subspace. Then in abnormal subspace, OD flows are grouped according to common destination address. At the same time, we compute statistical correlations between OD flows in each group and detect traffic anomaly behavior. Finally, we exploit traffic data from a real network to validate our method. Simulation results show that our approach can effectively and accurately detect OD traffic anomalies.

Published in:

Computational Problem-Solving (ICCP), 2010 International Conference on

Date of Conference:

3-5 Dec. 2010