Research on Secure Localization Model Based on Trust Valuation in Wireless Sensor Networks

Abstract

Secure localization has become very important in wireless sensor networks. However, the conventional secure localization algorithms used in wireless sensor networks cannot deal with internal attacks and cannot identify malicious nodes. In this paper, a localization based on trust valuation, which can overcome a various attack types, such as spoofing attacks and Sybil attacks, is presented. The trust valuation is obtained via selection of the property set, which includes estimated distance, localization performance, position information of beacon nodes, and transmission time, and discussion of the threshold in the property set. In addition, the robustness of the proposed model is verified by analysis of attack intensity, localization error, and trust relationship for three typical scenes. The experimental results have shown that the proposed model is superior to the traditional secure localization models in terms of malicious nodes identification and performance improvement.

Attacks classification and security mechanisms in Wireless Sensor Networks

“…• Secure Localization: In several applications, sensor networks are designed to locate faults. Consequently, the network must be able to accurately and automatically locate each sensor node that is why location information must be handled in a secure manner to avoid attacks taking advantage of the security weaknesses of this information [19].…”

A Hybrid Fuzzy System Based Cooperative Scalable and Secured Localization Scheme For Wireless Sensor Networks

“…A trust valuation based secured localization scheme has been proposed in [15] which was studied to be robust against spoofing, node duplication and Sybil attacks. The proposed scheme comprised of different types of trusts: Comprehensive trust (derived from average localization error and latency of anchors); direct trust (derived from belief of unknown sensor node in that beacon); and indirect trust (derived from location information an unknown node receives from its neighbors).…”

Routing Algorithm of Wireless Sensor Network and Robustness Analysis Based on Fuzzy Mathematics

“…However, there is still great room for improving the rationality of clustering, especially cluster head communication, without obvious increase in computing load [14]. For instance, the hierarchical design model can be introduced to consider the energy consumption, density and centrality of nodes prior to selecting cluster head.…”