Detecting Sybil Attack in Vehicular Ad-hoc Networks (Vanets) by Using Fitness Function, Signal Strength Index and Throughput

Ad-hoc networks are vehicular networks whose functions are widely expanding. High dynamicity and the presence of wireless communications are two major challenging features of these networks. Due to, security and protection of these networks have remained as big unresolved challenges. Attack detection in Vanets may have significant impact on the efficiency of these networks. Timely detection of attacks helps prevent road casualties and traffic control. Initial identification is done by the neighboring nodes. When each node receives a message from neighboring nodes, it compares the ID of each node's with those of other nodes' messages. If the messages are the same but sent from different nodes, neighboring nodes send a sample of the data to the RSU. If RSU doubts to an ID, it establishes a table of parameters, such a delay, packet drop and throughput. The total sum of fitness function should be equal to one. If the fitness function of these parameters is beyond the determined limit, nodes will continue to work. In this paper detected Sybil attacks used by the NS3 simulator. The results of the proposed method were acceptable in comparison with PDF (probability density function), FCVS (Fuzzy-based collaborative verification system) and Heartbeat scheme. Delay, energy and strength were the parameters, which had higher responsiveness.