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CLC number: TP393.08

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Received: 2003-12-05

Revision Accepted: 2004-04-21

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Cited: 119

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Journal of Zhejiang University SCIENCE A 2005 Vol.6 No.5 P.371-377


An immunity-based technique to detect network intrusions

Author(s):  PAN Feng, DING Yun-fei, WANG Wei-nong

Affiliation(s):  Department of Computer Science and Engineering, Shanghai Jiaotong University, Shanghai 200030, China; more

Corresponding email(s):   fpan@sjtu.edu.cn, pan_feng_hao@hotmail.com

Key Words:  Artificial immune system, Network intrusion detection, Negative selection, Clonal selection

PAN Feng, DING Yun-fei, WANG Wei-nong. An immunity-based technique to detect network intrusions[J]. Journal of Zhejiang University Science A, 2005, 6(5): 371-377.

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DOI - 10.1631/jzus.2005.A0371

This paper briefly reviews other people’s works on negative selection algorithm and their shortcomings. With a view to the real problem to be solved, authors bring forward two assumptions, based on which a new immune algorithm, multi-level negative selection algorithm, is developed. In essence, compared with Forrest’s negative selection algorithm, it enhances detector generation efficiency. This algorithm integrates clonal selection process into negative selection process for the first time. After careful analyses, this algorithm was applied to network intrusion detection and achieved good results.

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