Security and privacy solutions in intelligent transportation systems: A survey

In recent years, the automotive industry has experienced a digital revolution, with vehicles increasingly equipped with computer systems, transitioning from purely mechanical machines to sophisticated autonomous entities. This evolution extends beyond individual vehicles to encompass Intelligent Transportation Systems (ITS), fundamentally altering transportation networks. While these advancements promise enhanced efficiency, safety, and travel experience, they also introduce new challenges, particularly in security and privacy. For example, AI-based systems are now used for real-time congestion prediction, allowing for optimized traffic flow; and predictive car maintenance, minimizing breakdowns and enhancing safety. However, these systems can be vulnerable to cyberattacks and data breaches. Integrating diverse technologies into transportation systems offers undeniable benefits, but it also has vulnerabilities that are susceptible to exploitation by malicious actors. To address these concerns, a robust and privacy-conscious framework for ITS security is paramount. This paper provides a comprehensive overview of the current state of ITS research, focusing on security and privacy solutions. It proposes a taxonomy of security and privacy solutions, discusses challenges, and identifies future research directions to empower engineers and researchers in enhancing ITS security.