A Precise Algorithm for Detecting Malicious Sybil Nodes in Mobile Wireless Sensor Networks

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A Sybil attack, where a malicious node creates multiple fake or captured identities, is one of the most well-known attacks against wireless sensor networks (WSNs). This attack can leave devastating effects on operational and routing protocols, such as voting, data aggregation, resource allocation, and misbehavior detection. In this paper, a simple and precise algorithm for detecting Sybil attacks in mobile WSNs is proposed. Considering the rapid growth of Internet of Things (IoTs) devices and WSNs’ popularity, the threat from this attack is serious. The main underlying idea of the proposed algorithm is to use neighbors’ information and observer nodes to detect Sybil nodes during the network lifetime. In the proposed algorithm, some observer nodes first walk the network and record necessary information about other nodes. Each observer node then uses this collected information to detect Sybil nodes. The proposed algorithm is compared with other algorithms according to criteria including memory, communication, and computation overhead. Also, the proposed algorithm is implemented with the J-SIM simulator, and its performance is compared in a series of experiments with other algorithms using the criteria of true- and falsedetection rates. The simulation results indicate that the proposed algorithm can detect 100% of the Sybil nodes, so its false-detection rate is 0%, regarding the study assumptions.