Distributed clone detection in static Wireless Sensor Networks: Random Walk with Network Division

Khan, W.Z. and Aalsalem, M.Y. and Saad, N.M. (2015) Distributed clone detection in static Wireless Sensor Networks: Random Walk with Network Division. PLoS ONE, 10 (5).

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Abstract

Wireless Sensor Networks (WSNs) are vulnerable to clone attacks or node replication attacks as they are deployed in hostile and unattended environments where they are deprived of physical protection, lacking physical tamper-resistance of sensor nodes. As a result, an adversary can easily capture and compromise sensor nodes and after replicating them, he inserts arbitrary number of clones/replicas into the network. If these clones are not efficiently detected, an adversary can be further capable to mount a wide variety of internal attacks which can emasculate the various protocols and sensor applications. Several solutions have been proposed in the literature to address the crucial problem of clone detection, which are not satisfactory as they suffer from some serious drawbacks. In this paper we propose a novel distributed solution called Random Walk with Network Division (RWND) for the detection of node replication attack in static WSNs which is based on claimer-reporter-witness framework and combines a simple random walk with network division. RWND detects clone(s) by following a claimer-reporter-witness framework and a random walk is employed within each area for the selection of witness nodes. Splitting the network into levels and areas makes clone detection more efficient and the high security of witness nodes is ensured with moderate communication and memory overheads. Our simulation results show that RWND outperforms the existing witness node based strategies with moderate communication and memory overheads. © 2015 Khan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Item Type: Article
Impact Factor: cited By 18
Uncontrolled Keywords: adversary model; algorithm; analysis; area selection; Article; claim forwarding; clone detection; clone revocation; comparative study; computer model; computer network; computer security; computer simulation; distributed clone detection; heuristic algorithm; information processing; information processing device; line selected multicast algorithm; machine learning; memory overhead; network configuration; network model; probability; random walk with network division; randomized multicast algorithm; security analysis; static wireless sensor network; wireless communication; witness node; witness node selection; computer network; devices; information science, Algorithms; Computer Communication Networks; Computer Security; Computer Simulation; Information Theory; Wireless Technology
Depositing User: Ms Sharifah Fahimah Saiyed Yeop
Date Deposited: 26 Mar 2022 03:18
Last Modified: 26 Mar 2022 03:18
URI: http://scholars.utp.edu.my/id/eprint/31374

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