Alessio Buscemi, Thomas Engel (SnT, University of Luxembourg), Kang G. Shin (The University of Michigan)

The Controller Area Network (CAN) is widely deployed as the de facto global standard for the communication between Electronic Control Units (ECUs) in the automotive sector. Despite being unencrypted, the data transmitted over CAN is encoded according to the Original Equipment Manufacturers (OEMs) specifications, and their formats are kept secret from the general public. Thus, the only way to obtain accurate vehicle information from the CAN bus is through reverse engineering. Aftermarket companies and academic researchers have focused on automating the CAN reverse-engineering process to improve its speed and scalability. However, the manufacturers have recently started multiplexing the CAN frames primarily for platform upgrades, rendering state-of-the-art (SOTA) reverse engineering ineffective. To overcome this new barrier, we present CAN Multiplexed Frames Translator (CAN-MXT), the first tool for the identification of new-generation multiplexed CAN frames. We also introduce CAN Multiplexed Frames Generator (CANMXG), a tool for the parsing of standard CAN traffic into multiplexed traffic, facilitating research and app development on CAN multiplexing.

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Security-Performance Tradeoff in DAG-based Proof-of-Work Blockchain Protocols

Shichen Wu (1. School of Cyber Science and Technology, Shandong University 2. Key Laboratory of Cryptologic Technology and Information Security, Ministry of Education), Puwen Wei (1. School of Cyber Science and Technology, Shandong University 2. Quancheng Laboratory 3. Key Laboratory of Cryptologic Technology and Information Security, Ministry of Education), Ren Zhang (Cryptape Co. Ltd. and…

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Acoustic Keystroke Leakage on Smart Televisions

Tejas Kannan (University of Chicago), Synthia Qia Wang (University of Chicago), Max Sunog (University of Chicago), Abraham Bueno de Mesquita (University of Chicago Laboratory Schools), Nick Feamster (University of Chicago), Henry Hoffmann (University of Chicago)

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Gradient Shaping: Enhancing Backdoor Attack Against Reverse Engineering

Rui Zhu (Indiana University Bloominton), Di Tang (Indiana University Bloomington), Siyuan Tang (Indiana University Bloomington), Zihao Wang (Indiana University Bloomington), Guanhong Tao (Purdue University), Shiqing Ma (University of Massachusetts Amherst), XiaoFeng Wang (Indiana University Bloomington), Haixu Tang (Indiana University, Bloomington)

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Reminding Drivers of the Stalking Vehicles on the Road

Wei Sun, Kannan Srinivsan (The Ohio State University)

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