Autonomous vehicles play a significant role in future transportation systems by enabling driverless travel. These vehicles offer advantages such as reducing accidents, improving travel times, and conserving energy. However, ensuring the independent operation of these technologies requires robust cybersecurity measures. Protecting autonomous vehicles against security threats they may face within their internal systems or during communication with other vehicles and infrastructure is crucial. This study examines the security measures used in autonomous vehicles. Encryption and data protection techniques safeguard information from unauthorized access during in-vehicle and inter-vehicle communication. Additionally, intrusion detection and prevention systems (IDS/IPS) detect abnormal activities to protect against potential threats. Machine learning-based anomaly detection methods analyze data from sensors and network traffic to identify emerging threats. Regular software updates help mitigate vulnerabilities, while network segmentation isolates different systems to protect critical components. Multi-layered security solutions ensure the safe operation of autonomous vehicles. These approaches contribute to the development of future security standards.

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