The advent of fully autonomous vehicles (AVs) promises to reshape urban mobility improving efficiency and safety. Despite this, the dependency of AVs on Vehicle-to-Everything (V2X) communication networks introduces substantial cybersecurity vulnerabilities, including remote intrusions and data manipulation. This systematic review investigates strategies designed to safeguard data privacy and integrity within V2X communications, emphasizing the incorporation of ethical principles derived from Artificial Intelligence (AI) Ethics. The analysis indicates that while technical approaches, such as blockchain (BL) and Federated Learning (FL) are extensively adopted, the integration of ethical frameworks remains limited. In response, we propose twelve normative ethical principles aligned with international standards (e.g., IEEE, European Commission) to inform the responsible development and governance of AI systems in AVs. Our results demonstrate that the combination of BL and FL presents strong potential for developing secure, decentralized, and privacy-preserving V2X communication infrastructures.