Security Challenges and Solutions in Self‐Driving Vehicles: A Comprehensive Review

Self‐driving vehicles (SDVs), also known as autonomous vehicles, are at the forefront of technological advancements in transportation, offering significant benefits in safety, efficiency, and mobility. However, these vehicles face critical security challenges due to their reliance on sensors, artificial intelligence (AI), and networked communications. This paper presents a comprehensive review of the security challenges in SDVs, including cyberattacks on vehicular networks, sensor spoofing, AI‐based threats, and privacy concerns. Unlike previous reviews, this study systematically categorises security challenges and solutions based on their nature and impact, and presents a detailed tabular taxonomy of current solutions to cybersecurity threats, a conceptual threat model for SDVs’ system layers, the state‐of‐the‐art of SDVs’ architecture, and their relative effectiveness. Furthermore, the latest advancements, such as AI‐driven intrusion detection, blockchain‐based security mechanisms, lightweight cryptographic protocols, and hybrid approaches, are explored. Finally, the review highlights existing research gaps and suggests future directions for enhancing SDV security.