A comparative study of real-valued negative selection to statistical anomaly detection techniques

Thomas Stibor*, Jonathan Timmis, Claudia Eckert

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

112 Citations (Scopus)

Abstract

The (randomized) real-valued negative selection algorithm is an anomaly detection approach, inspired by the negative selection immune system principle. The algorithm was proposed to overcome scaling problems inherent in the hamming shape-space negative selection algorithm. In this paper, we investigate termination behavior of the real-valued negative selection algorithm with variable-sized detectors on an artificial data set. We then undertake an analysis and comparison of the classification performance on the high-dimensional KDD data set of the real-valued negative selection, a real-valued positive selection and statistical anomaly detection techniques. Results reveal that in terms of detection rate, real-valued negative selection with variable-sized detectors is not competitive to statistical anomaly detection techniques on the KDD data set. In addition, we suggest that the termination guarantee of the real-valued negative selection with variable-sized detectors is very sensitive to several parameters.

Original languageEnglish
Title of host publicationArtificial Immune Systems
Subtitle of host publication4th International Conference, ICARIS 2005, Banff, Alberta, Canada, August 14-17, 2005, Proceedings
PublisherSpringer Nature
Pages262-275
Number of pages14
Volume3627
DOIs
Publication statusPublished - 2005
Event4th International Conference on Artificial Immune Systems, ICARIS 2005 - Banff, Alta., Canada
Duration: 14 Aug 200517 Aug 2005

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Nature
ISSN (Print)0302-9743

Conference

Conference4th International Conference on Artificial Immune Systems, ICARIS 2005
Country/TerritoryCanada
CityBanff, Alta.
Period14 Aug 200517 Aug 2005

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