Research of CMABC Algorithm in Intrusion Detection
To the problem of the traditional parameters optimization algorithm may level into local optimal, a parameter optimization method crossover mutation artificial bee colony based on artificial bee colony algorithm is proposed to solve this problem and applied to intrusion detection. And introduced an improved artificial colony algorithm based on crossover mutation operator, the whole bee colony could be divided into two sub-populations according to the fitness value of colony and effectively avoid local optimum and enhance convergence speed, use standard test functions to verify the effectiveness of the algorithm. And the proposed algorithm’s performance is tested by the KDD-99 datasets, the experimental results show that this method can effective improve the classification performance of intrusion detection.
KeywordsIntrusion detection Support vector machine Artificial bee colony Crossover mutation
This research is supported in part by the National Natural Science Foundation of China under Grant Nos. 61262072.
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