Vehicle Network
Vehicle networks, primarily based on protocols like CAN and SOME/IP, are crucial for modern vehicle functionality and safety, but are vulnerable to both hardware failures and cyberattacks. Current research heavily focuses on developing robust anomaly detection systems using machine learning, particularly deep learning architectures like Graph Neural Networks, autoencoders, and variations of BERT, to identify malicious activities or malfunctions in real-time. These efforts are driven by the critical need to enhance vehicle security and reliability, impacting both automotive engineering and cybersecurity research through improved detection accuracy and resource-efficient model deployment.
Papers
November 15, 2024
September 11, 2024
August 25, 2024
February 21, 2024
November 14, 2023
February 3, 2023
October 17, 2022
July 21, 2022
July 11, 2022