Three factors based sybil attack detection and RSU corruption detection in the VANET environment

Vehicular Ad-Hoc Networks (VANET) handles transferring data betwixt moving vehicles to shun accidents and also render journey comfort along with traffic safety. However, the network is vulnerable mainly to the Sybil Attacks (SA). Though existing methodologies have conducted research on detecting the SA, the Network Lifetime (NLT) issues still exist. In addition, the prevailing methodology detects the attack centred on the location only. It doesn't offer an effectual outcome. In order to trounce such issues, this research methodology regards the '3' factors centred on SA as well as Road Side Unit (RSU) corruption detection on the VANET. Primarily, the entire vehicles are registered into the Trusted Authority (TA). After that, TA renders the location certificate utilizing RSU. Next, RSU checks whether the above 'l' location is found for a node, if yes, then the node is isolated, or else, it is considered for the communication. Then, the City Block-based Fuzzy C-Means (CBFCM) algorithm takes care of the cluster formation and Cluster Head (CH) selection. Next, the Chicken Swarm Optimization-Ad Hoc On-Demands Distances Vector (CSO-AODV) algorithm initializes the communication process. After that, the direct trust is computed; if the reply count is above 1, then the indirect trust is computed and the node is amassed on the blacklist, or else, the node is incorporated in the communication procedure.