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An Intrusion Detection Model Based on IPSO-SVM Algorithm in Wireless Sensor Network

Shuang Liu,
Liejun Wang,
Jiwei Qin,
Yan Guo,
Hang Zuo,

Abstract


Aiming at the energy constrained of wireless sensor network (WSN) and the low detection accuracy of intrusion detection mechanisms in WSN, an intrusion detection model based on improved Particle Swarm Optimization (IPSO) and Support Vector Machine (SVM) is proposed in this paper. Firstly, the improved LEACH algorithm is applied to our intrusion detection model to cluster the nodes to reduce energy consumption. Nextly, Anomaly detection based on SVM algorithm is used in this model to ensure that detector has a high detection accuracy. Finally, the SVM algorithm is optimized by using the IPSO algorithm to obtain the optimal SVM parameters, so as to improve the detection precision and convergence speed of the model. The experimental results show that the intrusion detection model mentioned in this paper has higher detection precision, faster convergence speed and more balanced use of node energy compared with other detection models.


Citation Format:
Shuang Liu, Liejun Wang, Jiwei Qin, Yan Guo, Hang Zuo, "An Intrusion Detection Model Based on IPSO-SVM Algorithm in Wireless Sensor Network," Journal of Internet Technology, vol. 19, no. 7 , pp. 2125-2134, Dec. 2018.

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