2025/07/19 by Franco Oberti, Oberti, Franco, Stefano Di Carlo +3
Computer Science · Engineering · #Autonomous Vehicle Technology and Safety #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Real-Time Systems Scheduling #Vehicular Ad Hoc Networks (VANETs)
paper · doi:10.48550/arxiv.2507.14739
openalex publication_date 2025/07/19 · openalex created_date 2025/12/01 · openalex updated_date 2026/07/28
The Controller Area Network (CAN) protocol, essential for automotive embedded systems, lacks inherent security features, making it vulnerable to cyber threats, especially with the rise of autonomous vehicles. Traditional security measures offer limited protection, such as payload encryption and message authentication. This paper presents a novel Intrusion Detection System (IDS) designed for the CAN environment, utilizing Hardware Performance Counters (HPCs) to detect anomalies indicative of cyber attacks. A RISC-V-based CAN receiver is simulated using the gem5 simulator, processing CAN frame payloads with AES-128 encryption as FreeRTOS tasks, which trigger distinct HPC responses. Key HPC features are optimized through data extraction and correlation analysis to enhance classification efficiency. Results indicate that this approach could significantly improve CAN security and address emerging challenges in automotive cybersecurity.