A new model of self-adaptive network intrusion detection

A new model of self-adaptive network intrusion detection based on negative selection algorithm is presented to tackle the problem of self continuously changeable in network intrusion detection. The evolvement of self is fully expounded; a new method that generates and evolves detectors is put forwar...

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Bibliographic Details
Published in2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence) pp. 436 - 439
Main Authors Zhang, Qing-hua, Fu, Yu-zhen, Xu, Bu-gong
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2008
Subjects
artificial immune
Evolutionary computation
intrusion detection
negative selection algorism
Self-adaptive
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Summary:A new model of self-adaptive network intrusion detection based on negative selection algorithm is presented to tackle the problem of self continuously changeable in network intrusion detection. The evolvement of self is fully expounded; a new method that generates and evolves detectors is put forward, which can update automatically to keep synchronization with self. The result shows that the model has the properties of self-adaptability & dynamics, and can identify the intrusion effectively.
ISBN:1424418224
9781424418220
ISSN:1089-778X
1941-0026
DOI:10.1109/CEC.2008.4630834