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

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3 Author(s)
Xiang-Rong Yang ; Dept. of Comput. Sci. & Technol., Xi''an Jiaotong Univ., China ; Jun-Yi Shen ; Rui Wang

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.

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Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on  (Volume:1 )

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