Digital Twins with Blockchain Model Based Trust and Reputation Scoring Mechanism for Enhanced VANET Routing Protocol

Today, Vehicular Ad hoc Networks (VANETs) have great attention because of their capability to offer quality intelligent systems to remote locations. Although VANETs get more distributed and network diagrams become more sophisticated, the possibility of failure increases, notably in terms of security. Blackhole attacks are common attacks that indeed severely impact network performance and disrupt vehicle communication. Various techniques have been developed to discover blockhole lists and diminish malicious nodes that exploit reputation systems. However, when multiple malicious nodes are present in the network, additional challenges arise, such as broadcast message tampering attacks and packet dropping, which can hinder the dissemination of messages. The main objective of this work is to introduce a decentralized trust scoring system that relies on the consolidation of blockchain with digital twins (DTwins) to evaluate and preserve the reputation and behavioral patterns of vehicles where the presence of malicious nodes is exposed, and the process of decision-making is made seamless. The routing scheme implemented in this work utilizes an Ad-hoc On-Demand Vector (AODV) to assess the trustworthiness of neighboring nodes. Trust within this routing protocol is estimated by considering diverse metrics related to the routing protocol, including packet delivery ratio, computation cost, network throughput, and delay time, which demonstrates superior performance to other schemes by 61.73% to 40.37%. Experiments with network and traffic simulators estimated the security risk and the system's operational agility. The evaluation process illustrates the significance of reputation systems by showing the probability of having a decentralized system relying on blockchain to hold and disseminate reputation scores.