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Abstract: Vehicular Ad-Hoc Networks (VANETs) play a crucial role in the development of Intelligent Transportation Systems (ITS), facilitating efficient and secure communication between vehicles. The dynamic and open nature of VANETs poses significant challenges to security and privacy. This study explores the integration of blockchain technology and privacy- preserving mechanisms in VANETs, leveraging a hybrid optimization algorithm combining Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO), referred to as PSOACO. The proposed method aims to enhance the security and privacy of communication within VANETs. In this project, we employ Extreme Gradient Boosting Classifier (ETC) and Random Forest Classifier (RF) to evaluate the performance of the proposed approach. The results demonstrate that the ETC classifier achieves an accuracy of 96%, while the RF classifier achieves an accuracy of 95%.