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Issue title: Recent advancements in computer, communication and computational sciences
Guest editors: K.K. Mishra
Article type: Research Article
Authors: Wang, Huaa | Wen, Yingyoua; b | Zhao, Dazhea; c; *
Affiliations: [a] School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China | [b] State Key Laboratory of Software Architecture, Neusoft Corporation, Shenyang, China | [c] Key Laboratory of Medical Image Computing, Ministry of Education, Northeastern University, Shenyang, China
Correspondence: [*] Corresponding author. Dazhe Zhao, Tel.: +86 0248 3661 727; Fax: +86 0248 3663 446; E-mail: zhaodazhe@mail.neu.edu.cn.
Abstract: In this paper, we study the problem of secure localization in Mobile Wireless Sensor Networks (MWSNs) where beacon nodes are not available. The location reference information is obtained from neighboring nodes within the commination rage of the target node, with the help of a relative location map. A Relative Location Map based Robust Positioning Algorithm (RLMRPA) for MWSNs is presented. The location estimate of the localizing node is formulated by constructing a distance measurement error model. Considering limited resources available, the steepest descent, which is fast and easy to implement, is employed to iteratively find the optimal solution. A 3- Farthest Neighbors Trilateral Localization Algorithm (3FNTLA) is presented to find the initial position. Considering that malicious neighbors tend to cause larger distance measurement errors and the further the neighbor, the larger the measurement error, an attack-resistant distance residue method is developed to neutralize the impact of inconsistent measurements. Our experiments show that the RLMRPA can perform secure location determination, even with some neighbors aiming at making the localization failed. In addition, our simulation results also demonstrate that the RLMRPA is more resistant to attacks and achieves higher localization accuracy than existing methods.
Keywords: Mobile wireless sensor networks, localization, threats, security
DOI: 10.3233/JIFS-169303
Journal: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 5, pp. 3695-3710, 2017
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