Enriched Model of Pigeon Inspired Pseudonym Generation for Privacy Preservation of Vehicles Location in VANET

Vehicular Ad Hoc Networks are networks of vehicles interconnected by an incredibly dynamic structure in an unpredictable atmosphere. In VANET communication is done by message broadcasting and emergency communications will also be sent between vehicles using this most basic form of communication. Due to its open network, it leads to high risk of tampering identity of the vehicle’s location which is the emerged as a key research area of intelligent transports system. Researchers developed many algorithms to handle the issue of reserving the identity of the vehicular nodes using pseudonym method. But, the problem of preserving identity of the source vehicles is still a challenging issue due to its dynamic environment. Hence, in this paper an enriched metaheuristic model is constructed to achieve optimal solution in detection of most promising vehicles, that are able to preserve the identity of vehicles location more strongly. The pigeon inspired optimization algorithm is used for generating Pseudonym identity, instead of using random generator as in standard models. The message to be transferred is also encrypted for offering reliable security. The simulation results proved that the proposed Enriched Pigeon Inspired Optimization (EPIO) effectively performs location identity preserving using pseudonym in VAENT by alleviating the issue security breaches and privacy preservation problem.