Full Text:
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CLC number: TP393.08
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 0000-00-00
Cited: 119
Clicked: 6405
An immunity-based technique to detect network intrusions
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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.
@article{title="An immunity-based technique to detect network intrusions",
author="PAN Feng, DING Yun-fei, WANG Wei-nong",
journal="Journal of Zhejiang University Science A",
volume="6",
number="5",
pages="371-377",
year="2005",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2005.A0371"
}
%0 Journal Article
%T An immunity-based technique to detect network intrusions
%A PAN Feng
%A DING Yun-fei
%A WANG Wei-nong
%J Journal of Zhejiang University SCIENCE A
%V 6
%N 5
%P 371-377
%@ 1673-565X
%D 2005
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2005.A0371
TY - JOUR
T1 - An immunity-based technique to detect network intrusions
A1 - PAN Feng
A1 - DING Yun-fei
A1 - WANG Wei-nong
J0 - Journal of Zhejiang University Science A
VL - 6
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SP - 371
EP - 377
%@ 1673-565X
Y1 - 2005
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.2005.A0371
Abstract: 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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