By Topic

An Unsupervised Intrusion Detection Method Combined Clustering with Chaos Simulated Annealing

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)
Lin Ni ; Chongqing Univ., Chongqing ; Hong-Ying Zheng

Keeping networks security has never been such an imperative task as today. Threats come from hardware failures, software flaws, tentative probing and malicious attacks. In this paper, a new detection method, Intrusion Detection based on Unsupervised Clustering and Chaos Simulated Annealing algorithm (IDCCSA), is proposed. As a novel optimization technique, chaos has gained much attention and some applications during the past decade. For a given energy or cost function, by following chaotic ergodic orbits, a chaotic dynamic system may eventually reach the global optimum or its good approximation with high probability. To enhance the performance of simulated annealing which is to find a near-optimal partitioning clustering, simulated annealing algorithm is proposed by incorporating chaos. Experiments with KDD cup 1999 show that the simulated annealing combined with chaos can effectively enhance the searching efficiency and greatly improve the detection quality.

Published in:

Machine Learning and Cybernetics, 2007 International Conference on  (Volume:6 )

Date of Conference:

19-22 Aug. 2007