Accurate detection of selective forwarding attack in wireless sensor networks

Qiong Zhang and Wenzheng Zhang

International Journal of Distributed Sensor Networks, 2019, vol. 15, issue 1, 1550147718824008

Abstract: Selective forwarding attack in wireless sensor networks shows great impact on network performance and consumes limited energy resource. In previous countermeasures, it is assumed that all nodes in the communication range can detect misbehaviors of the attacker. However, as wireless devices require certain signal-to-noise ratio to receive frames correctly, and interference among nodes is inevitable in densely deployed wireless sensor networks, it is very difficult for previous approaches to detect misbehaviors accurately. In this article, a scheme named E-watchdog is proposed to improve accuracy of selective forwarding attack detection. Detection agents that are closer to the attacker are used to detect misbehaviors, which can improve the detection accuracy and reduce the false alarm rate effectively. Moreover, to prevent collaborative selective forwarding attack, E-watchdog uses reports from more than one detection agents. Fake reports from attackers are filtered out through an election algorithm. Simulation results show that the E-watchdog reduces the false detection rate by 25% and improves the detection accuracy by 10% on the premise of increasing negligible energy consumption.

Keywords: Wireless sensor networks; selective forwarding attack; signal to noise ratio; detection accuracy (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:15:y:2019:i:1:p:1550147718824008

DOI: 10.1177/1550147718824008

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