Abstract
On the basic of multiple populations of immune algorithm and clonal selectionalgorithm, the purpose of this paper is to further improve the detectionefficiency and reducing the false alarm rate. This paper uses the kddcup99 dataset as the experimental data set, and chooses four types of attack data groupof experiment data set as initial population of multiple populations of clonalselection algorithm, through the algorithm to create the optimal model. Basedon the principle of normal data larger than the abnormal data, in turn,experimental data set matched with the normal data set and the optimal model bythe improved R matching algorithm. The results of this paper show that thedetection rate increased significantly
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