A New Lightweight Watchdog-Based Algorithm for Detecting Sybil Nodes in Mobile WSNs

Rezvan Almas Shehni, Karim Faez, Farshad Eshghi and Manoochehr Kelarestaghi
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Rezvan Almas Shehni: Department of Computer Engineering and Information Technology, Qazvin Azad University, Qazvin 15195-34199, Iran
Karim Faez: Department of Electrical Engineering, Amirkabir University of Technology, Tehran 15916-34311, Iran
Farshad Eshghi: Department of Electrical & Computer Engineering , Faculty of Engineering, Kharazmi University, Tehran 15719-14911, Iran
Manoochehr Kelarestaghi: Department of Electrical & Computer Engineering , Faculty of Engineering, Kharazmi University, Tehran 15719-14911, Iran

Future Internet, 2017, vol. 10, issue 1, 1-17

Abstract: Wide-spread deployment of Wireless Sensor Networks (WSN) necessitates special attention to security issues, amongst which Sybil attacks are the most important ones. As a core to Sybil attacks, malicious nodes try to disrupt network operations by creating several fabricated IDs. Due to energy consumption concerns in WSNs, devising detection algorithms which release the sensor nodes from high computational and communicational loads are of great importance. In this paper, a new computationally lightweight watchdog-based algorithm is proposed for detecting Sybil IDs in mobile WSNs. The proposed algorithm employs watchdog nodes for collecting detection information and a designated watchdog node for detection information processing and the final Sybil list generation. Benefiting from a newly devised co-presence state diagram and adequate detection rules, the new algorithm features low extra communication overhead, as well as a satisfactory compromise between two otherwise contradictory detection measures of performance, True Detection Rate (TDR) and False Detection Rate (FDR). Extensive simulation results illustrate the merits of the new algorithm compared to a couple of recent watchdog-based Sybil detection algorithms.

Keywords: mobile WSN; security; watchdog node; Sybil attack (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2017
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