(Enter summary)
Abstract: This paper explores the use of an artificial
immune system (AIS) for network intrusion detection.
As one significant component for a complete AIS, static
clonal selection with a negative selection operator is
developed and the system is described in detail. Two
important factors, the detector sample size and the
antigen sample size, are investigated in order to
generate an appropriate mixture of general and
specific detectors for learning non-self antigen
patterns. By investigating the results... (Update)
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BibTeX entry: (Update)
J. Kim and P.J. Bentley. The Artificial Immune System for Network Intrusion Detection: An Investigation of Clonal Selection with Negative Selection Operator. The Congres on Evolutionary Computation (CEC2001) , Seoul, Korea, pp. 1244-1252, May 27-30. http://citeseer.ist.psu.edu/article/kim01artificial.html More
@inproceedings{ kim99artificial,
author = "Jungwon Kim",
title = "An artificial immune system for network intrusion detection",
booktitle = "Graduate Student Workshop",
month = "13",
address = "Orlando, Florida, USA",
editor = "Una-May O'Reilly",
pages = "369--370",
year = "1999",
url = "citeseer.ist.psu.edu/article/kim01artificial.html" }
Citations not processed or no citations identified.
Documents on the same site (http://www.dcs.kcl.ac.uk/staff/jungwon/publication.html): More
An Evaluation of Negative Selection in an Artificial Immune.. - Kim, Bentley (2001)
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New Trends in Evolutionary Computation - Bentley, Gordon, Kim, Kumar (2001)
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Towards an Artificial Immune System for Network Intrusion.. - Kim, Bentley (2002)
(Correct)
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