Title :
A Novel Method of Intrusion Detection Based on Artificial Immune System
Author :
Zhang, Yu-fang ; Sun, Gui-hua ; Xiong, Zhong-Yang
Author_Institution :
Coll. of Comput., Chongqing Univ.
Abstract :
This paper presents a novel method of intrusion detection based on artificial immune system. Adopting the constraint-based detectors and any-r intervals matching rule, a novel solution is presented to encode the antibody-antigen. Some immune related concepts are introduced. In order to accelerate the accessing of the normal IP packets, the self-pattern class is proposed. Using the data sets of KDD CUP1999, the experiment results show that the proposed method can achieve a faster running speed and better detecting rates. It also can adapt to dynamically changing environments
Keywords :
IP networks; fault tolerant computing; security of data; telecommunication security; IP packet; antibody-antigen encoding; artificial immune system; constraint-based detector; intrusion detection method; matching rule; Artificial immune systems; Bones; Condition monitoring; Cybernetics; Detectors; Humans; Immune system; Information security; Intrusion detection; Machine learning; Pathogens; Protection; Sun; Antigen-antibody; any-r intervals matching rule; constraint-based detectors; self-pattern class;
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
DOI :
10.1109/ICMLC.2006.258837
