Research on the Detection of Network Intrusion Prevention With Svm Based Optimization Algorithm

Debing Wang, Guangyu Xu


Support vector machine (SVM) has a good application in intrusion detection, but its performance needs to be further improved. This study mainly analyzed the optimization algorithm of SVM. Firstly, the principle of SVM was introduced, then SVM was improved using whale optimization algorithm (WOA), the WOA was improved, the intrusion detection method based on IWOA-SVM was analyzed, and experiments were carried out on KDD CUP99 to verify the effectiveness of the algorithm. The results showed that the IWAO-SVM algorithm was more accurate in attack detection; compared with SVM, PSO-SVM and ACO-SVM algorithms, the performance of the IWAO-SVM algorithm was better, the detection rate was 99.89%, the precision ratio was 99.92%, the accuracy rate was 99.86%, and the detection time was 192 s, showing that it had high precision in intrusion detection. The experimental results verify the reliability of the IWAO-SVM algorithm, and it can be promoted and applied in the detection of network intrusion prevention.

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