Multi-agent trust-based intrusion detection scheme for wireless sensor networks. (April 2017)

• Record Type: Journal Article
• Authors: Jin, Xianji; Liang, Jianquan; Tong, Weiming; Lu, Lei; Li, Zhongwei
• Is Part Of: Computers & electrical engineering. Volume 59(2017)
• Page Start: 262
• Page End: 273
• Publication Date: 2017-04
• Subjects: Wireless sensor networks -- Intrusion detection -- Multi-agent -- Node trust value; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2017.04.013
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: A trust based intrusion detection scheme in layer-cluster WSNs is proposed. The implementation of this scheme is based on Multi-agent framework. The node trust feature abnormality is judged by Mahalanois distance. Tolerance factor q is introduced in trust value calculation. Abstract: In order to achieve both a higher detection rate and a lower false positive rate of internal node intrusion detection in layer-cluster wireless sensor networks, an intrusion detection scheme based on the use of both a multi-agent system and a node trust value is proposed. In this scheme, the multi-agent model framework is established in both the cluster heads and the ordinary sensor nodes to perform intrusion detection. First, various, typical node trust attributes are defined and Mahalanobis distance theory is used to judge whether these attributes are normal. Second, the node trust value is calculated and updated based on the combination of the Beta distribution and a tolerance factor. Finally, node intrusion detection is realized. Simulation results demonstrate that the modified scheme has a higher detection rate and a lower false positive rate, even when several types of intrusions are present. Graphical abstract: