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Connected and automated vehicles (CAVs) are becoming a reality. Prototyping and testing of self-driving vehicle technology are becoming more popular around the world. The secure deployment of self-driving vehicles necessitates a wide range of technology, competencies, and procedures, all of which must be thoroughly checked and assessed, as road safety may be a risk. As a result, it’s critical to recognize and develop a thorough understanding of the cyber security and privacy concerns with CAVs and of the way these can be prioritized as well as addressed. This chapter investigates falsified information attacks against the RSU’s ongoing FL operation. We discovered a variety of attack tactics used by malicious CAVs to disrupt global system training in vehicular ad hoc networks (VANETs). In which, demonstrate the attacks effectively increased the convergence time and reduced the model’s accuracy.