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Exploiting dispersive power gain and delay spread for sybil detection in industrial WSNs

Industrial Wireless Sensor Networks (IWSNs), as a kind of flexible platform to monitor machinery status and enhance industrial automation, bring enormous benefits in manufacturing, automated metering, conditioned-based maintenance and inventory, etc. However, security threats, such as Sybil attacks, hinder the flourish of IWSNs, since they are hardly detected in the harsh industrial environments with dispersive distortion, impulse noise and interference. In this paper, we propose a Sybil detection scheme in IWSNs, called PGDS, based on power gain and delay spread exacted from receiving packets. For wireless channel model, we consider the significant effects of impulse noise, interference, vibrating obstacle and user mobility. The Sybil packets are detected by classifying the channel-vector obtained by power gain and delay spread from each sensor. An adapter factor is utilized to enhance the detection accuracy. Security analysis demonstrates that the PGDS can detect the packets from Sybil attackers when they adaptively change the transition power. Simulation results with an increasing number of sensors show that the PGDS with lower value of adaptor factor can detect the packets from Sybil attackers with high accuracy.