Blockchain-based data storage and data sharing contract in vehicle edge computing using adaptive deep deterministic policy gradient

In the efficient growth of Vehicular Ad Hoc Networks (VANETs), the performance of data transmission and protection is crucial for improving smooth communication. Yet, it is insufficient for accurately handling a huge amount of user data to address the aforementioned issues in the training phase, and it reduces the security level of secured data; thus, it makes it more vulnerable to malicious activities and hackers for damaging the entire system. Therefore, the Vehicle Edge Computing (VEC) platform is employed in this research work, which can potentially minimize the delay of the computation tasks to ensure long-term utility of the system at time-varying communication conditions. Also, it can manage a large quantity of input data without any interference for dynamically mitigating privacy and security burdens to guarantee the data transmission performance. However, the Roadside Units (RSUs) used as automobile edge computing servers cannot be completely trusted, as they lead to privacy and protection issues. Here, a blockchain-based VEC mechanism is designed to ultimately protect the low-latency data, and it can quickly mitigate unauthorized access’s performance to make better trustworthy and efficient. VEC consists of some RSUs, and the data collected from these RSUs is stored in a blockchain. Then, Adaptive Efficient Capsnet (AE-CapsNet) is designed for the authentication process of blocks, which reduces the risk of fraud and unauthorized nodes in the network. Finally, secure VEC is done with the help of Adaptive Deep Deterministic Policy Gradient (A-DDPG), and the reliability of this designed approach is maximized by optimizing the parameters from A-DDPG by utilizing Improved Random Variable-based Fennec Fox Optimization (IRV-FFO). At last, the entire process of the designed approach is validated and compared with existing methodologies based on various metrics.