Matteo Frigo
Matteo Frigo received the B.E. degree from the University of Trento, Trento, Italy, in 2024. He is currently pursuing the M.E. degree in Cybersecurity Engineering at the Polytechnic University of Turin, Turin, Italy.
His main research interests include cybersecurity, automotive security, and machine learning.
Session
Most automotive security research still relies on manual or semi-automated processes to reverse-engineer CAN bus protocols and reveal how vehicle data such as speed, acceleration, or throttle position is encoded. We present a novel, fully automated approach that instantly identifies the bits corresponding to physical vehicle features, even on previously unseen models, by analyzing physics-based relationships reflected in raw CAN traffic. Our method accelerates reverse engineering from hours or days to mere minutes. We explore the impact of such fully-automated passive reverse engineering not only for vehicles but also for other CPS/OT environements.