Network Intrusion Detection Model Based on Genetic Algorithm Optimizing Parameters of Support Vector Machine

Chun Liu · Advanced materials research · 2014

Intrusion detection is an emerging area of research in the computer security and networks with the growing usage of internet in everyday life. Parameters selection of support vector machine is a important problems in network intrusion detection. In order to improve network intrusion detection precision, this paper proposed a network intrusion detection model based on parameters of support vector machine (SVM) by genetic algorithm. The performance of the model was tested by KDD Cup 99 data. Compared with other network intrusion detection models, the proposed model has significantly improved the detection precision of network intrusion.

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