CYBERSECURITY CHALLENGES AND DEFENSE MECHANISMS IN AUTONOMOUS VEHICLES: PROTECTING CONNECTED AND INTELLIGENT TRANSPORTATION SYSTEMS FROM EMERGING CYBER THREATS

Abstract

The concept of autonomous vehicles (AVs) has introduced a new and advanced technology in the field of intelligent transportation systems. It has the potential to integrate artificial intelligence, sensor technologies, and communication systems. However, the increased level of connectivity and dependency on digital technologies have led to the emergence of various cybersecurity threats. Malicious actors can take advantage of the vulnerabilities in the communication network of the vehicles and the architecture of the autonomous vehicles. This paper identifies the major cybersecurity threats in the context of autonomous vehicles. They include Controller Area Network (CAN) attacks, denial-of-service (DoS) attacks, GPS spoofing, and the vulnerability of the vehicle-to-everything (V2X) communication. A multilayered cybersecurity architecture based on encryption, authentication, and intrusion detection using machine learning has been proposed. The effectiveness of the proposed architecture has been validated through experimentation using the simulated network traffic of the autonomous vehicles. It has demonstrated the potential of the Random Forest algorithm in detecting malicious activities in the network.