Reference : CANMatch: A Fully Automated Tool for CAN Bus Reverse Engineering based on Frame Matching
Scientific journals : Article
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/48502
CANMatch: A Fully Automated Tool for CAN Bus Reverse Engineering based on Frame Matching
English
Buscemi, Alessio mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS) >]
Turcanu, Ion [Luxembourg Institute of Science & Technology - LIST > ITIS]
Castignani, German [University of Luxembourg]
Crunelle, Romain [Xee / Eliocity SAS]
Engel, Thomas [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS) >]
2-Nov-2021
IEEE Transactions on Vehicular Technology
Institute of Electrical and Electronics Engineers
Yes (verified by ORBilu)
International
0018-9545
United States
[en] CAN Bus ; Automated Reverse Engineering ; In-Car Networking ; Tokenization
[en] Controller Area Network (CAN) is the most frequently used in-vehicle communication system in the automotive industry today. The communication inside the CAN bus is typically encoded using proprietary formats in order to prevent easy access to the information exchanged on the bus. However, it is still possible to decode this information through reverse engineering, performed either manually or via automated tools. Existing automated CAN bus reverse engineering methods are still time-consuming and require some manual effort, i.e., to inject diagnostic messages in order to trigger specific responses. In this paper, we propose CANMatch a fully automated CAN bus reverse engineering framework that does not require any manual effort and significantly decreases the execution time by exploiting the reuse of CAN frames across different vehicle models. We evaluate the proposed solution on a dataset of CAN logs, or traces, related to 479 vehicles from 29 different automotive manufacturers, demonstrating its improved performance with respect to the state of the art.
Fonds National de la Recherche - FnR
Researchers ; Professionals ; Students
http://hdl.handle.net/10993/48502
10.1109/TVT.2021.3124550
FnR ; FNR10621687 > Sjouke Mauw > SPsquared > Security And Privacy For System Protection > 01/01/2017 > 30/06/2023 > 2015

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