ABSTRACT The Internet of Vehicles (IoV) is frequently utilized in the quick advancement of communication and computing technologies. The amount of data received from IoV networks has increased dramatically because of the IoV's quick development. The developments of technology assist drivers, automakers, and insurance providers in exchanging important data about connected cars for a variety of uses. The IoV has emerged in recent days as a result of lower costs, faster data transfer, and minimal latency. The heterogeneous nature of IoV initiates notable security and trust issues. The blockchain is a significant tool that resolves the downsides of the baseline Proof‐of‐Work (PoW). Blockchain technology provides a powerful technique for handling security and trust issues in IoV platforms. Especially, this work examines the capability of blockchain technology for enhancing the communication among independent vehicles. It establishes the trustworthiness of data transmission among one or more systems through the utilization of blockchain‐based systems. In this work, a blockchain‐based secure framework is developed for the IoV environment with the support of classifiers to mitigate network layer attacks. This proposed model efficiently detects attacks and malicious nodes in the network, which helps to prevent accidents. Here, the Blockchain consensus with Proof of Consultative Validation (BCPoCV) is performed to secure the IoV information based on trust score detection. Moreover, the presence of a malicious node and the network layer attack, such as DDoS attacks in the node, is determined using the Adaptive Temporal Convolutional Networks with Multilevel Attention (ATCN‐MA) model to determine the trust score. It enhances the detection accuracy and ignores the irrelevant information from the IoV environment. In addition to this, the parameter in the model is tuned using the Sorted Fitness‐Oriented Lyrebird Optimization (SFO‐LO) to enhance the prediction result. The parameter optimization process SFO‐LO algorithm deduces the computational complexity and enhances detection accuracy. This framework detected the DDoS attack in the network layer using the developed method. The comparative validation is done by several performance metrics. The suggested SFO‐LO‐ATCN‐MA model attained 97% accuracy in detecting the attacks on the layers of the IoV. Thus, the proposed blockchain‐based secure IoV framework explores the strength of security and authentication that can help to prevent attacks.
Tiwari et al. (Thu,) studied this question.