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BEGIN:VEVENT
DTSTAMP:20260402T024532Z
LOCATION:3008\, Level 3
DTSTART;TZID=America/Los_Angeles:20250624T103000
DTEND;TZID=America/Los_Angeles:20250624T104500
UID:dac_DAC 2025_sess154_RESEARCH837@linklings.com
SUMMARY:On Bit-level Reverse Engineering of Vehicular CAN Bus
DESCRIPTION:Yunlang Cai, Hanxue Shi, Xiaohang Wang, Haoting Shen, Li Lu, a
 nd Kui Ren (Zhejiang University)\n\nThe Controller Area Network (CAN) bus 
 is a cornerstone of modern vehicles, orchestrating functions from engine c
 ontrol to auxiliary systems. However, its lack of inherent security measur
 es makes it vulnerable to cyberattacks. Accurately mapping CAN signals wit
 h car-control actions is critical for detecting security breaches, as it a
 llows pinpointing potential vulnerabilities exploited to compromise vehicu
 lar functions. Despite this, existing CAN reverse engineering methods stru
 ggle to achieve bit-level resolution due to the huge search space of uniqu
 e IDs and payload combinations. To address this challenge, we propose a sy
 stematic framework for reverse engineering CAN bus messages, achieving pre
 cise mapping of control bits in CAN frames to car-control actions. The fra
 mework was validated on Tesla Model 3, Leapmotor C10 and C11, demonstratin
 g its versatility across different vehicle platforms. In particular, it su
 ccessfully identified 43 car-control actions on the Tesla Model 3, showcas
 ing its extensive coverage. Furthermore, its low resource consumption enab
 les seamless integration into compact platforms like the Raspberry Pi, sup
 porting practical deployment in real-world automotive systems.\n\nTopics: 
 Security\n\nTracks: SEC4: Embedded and Cross-Layer Security\n\nSession Cha
 irs: Hang Lu (State Key Laborotary of Computer Architecture, Institute of 
 Computing Technology, Chinese Academy of Sciences) and Fengwei Zhang (Sout
 hern University of Science and Technology, SUSTech)\n\n
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