Negative Selection Algorithm Based on Double Matching Rules

Yu Hu; Bin Li

doi:10.4028/www.scientific.net/AMR.204-210.42

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 204-210Negative Selection Algorithm Based on Double...

Negative Selection Algorithm Based on Double Matching Rules

Abstract:

The theory of artificial immune had been widely used in the research of network intrusion detection. Nowadays, the existing detector generating algorithms based on negative selection usually use a certain matching rule, as a result, too many detectors may generate, and the false alarm rate will become more serious. This paper proposes an improved negative selection algorithm using double matching rule: candidate detectors should be selected by the improved Hamming distance matching first, then the remaining detectors go through the segmented r-chunks(rch) matching rule. Experiments show that compared with traditional algorithms, this method brings a small number and more efficient detectors, reduces the false alarm rate and guarantees the efficiency of detectors.

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Periodical:

Advanced Materials Research (Volumes 204-210)

Pages:

42-45

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.204-210.42

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Online since:

February 2011

Authors:

Yu Hu, Bin Li

Keywords:

Artificial Immune, Detectors, Double Matching, Intrusion Detection, Negative Selection

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References

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