Computer Science ›› 2018, Vol. 45 ›› Issue (2): 231-235, 260.doi: 10.11896/j.issn.1002-137X.2018.02.040

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Novel Network Intrusion Detection Method Based on IPSO-SVM Algorithm

MA Zhan-fei, CHEN Hu-nian, YANG Jin, LI Xue-bao and BIAN Qi   

  • Online:2018-02-15 Published:2018-11-13

Abstract: Network intrusion detection has always been the research focus in the field of computer network security,and the current network is facing many potential security problems.In order to improve the accuracy of network intrusion detection,this paper improved the particle swarm optimization (PSO) algorithm,and then optimized the parameters of support vector machine (SVM) by using the improved PSO algorithm.On this basis,this paper also designed a novel network intrusion detection method based on IPSO-SVM algorithm.The experiment results show that the proposed IPSO-SVM algorithm is efficient.Compared with the classical SVM algorithm and PSO-SVM algorithm,IPSO-SVM algorithm not only improves the convergence speed of the network training obviously,but also improves the accuracy rate of network intrusion detection by 7.78% and 4.74% respectively,decreases the false positive rate by 3.37% and 1.19%,and decreases the false negative rate by 1.46% and 0.66%.

Key words: Network security,Intrusion detection,Particle swarm optimization algorithm,Optimal parameter,Support vector machine

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