Artificial immune theory based network intrusion detection system and the algorithms design

A network intrusion detection model based on artificial immune theory is proposed in this paper. In this model, self patterns and non-self patterns are built upon frequent behaviors sequences, then a simple but efficient algorithm for encoding patterns is proposed. Based on the result of encoding, a...

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Main Authors: Xiang-Rong Yang, Jun-Yi Shen, Rui Wang
Format: Conference Proceeding
Language:English
Subjects:
Algorithm design and analysis
Biology computing
Computer science
Computer security
Condition monitoring
Detectors
Encoding
Humans
Immune system
Intrusion detection
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Jun-Yi Shen
Rui Wang
description A network intrusion detection model based on artificial immune theory is proposed in this paper. In this model, self patterns and non-self patterns are built upon frequent behaviors sequences, then a simple but efficient algorithm for encoding patterns is proposed. Based on the result of encoding, another algorithm for creating detectors is presented, which integrates a negative selection with the clonal selection. The algorithm performance is analyzed, which shows that this method can shrink each generation scale greatly and create a good niche for patterns evolving.
doi_str_mv 10.1109/ICMLC.2002.1176712
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subjects Algorithm design and analysis
Biology computing
Computer science
Computer security
Condition monitoring
Detectors
Encoding
Humans
Immune system
Intrusion detection
title Artificial immune theory based network intrusion detection system and the algorithms design
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