Article (Scientific journals)
CANMatch: A Fully Automated Tool for CAN Bus Reverse Engineering based on Frame Matching
Buscemi, Alessio; Turcanu, Ion; Castignani, German et al.
2021In IEEE Transactions on Vehicular Technology
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Keywords :
CAN Bus; Automated Reverse Engineering; In-Car Networking; Tokenization
Abstract :
[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.
Disciplines :
Computer science
Author, co-author :
Buscemi, Alessio ;  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)
External co-authors :
yes
Language :
English
Title :
CANMatch: A Fully Automated Tool for CAN Bus Reverse Engineering based on Frame Matching
Publication date :
02 November 2021
Journal title :
IEEE Transactions on Vehicular Technology
ISSN :
0018-9545
Publisher :
Institute of Electrical and Electronics Engineers, United States
Peer reviewed :
Peer Reviewed verified by ORBi
FnR Project :
FNR10621687 - Security And Privacy For System Protection, 2015 (01/01/2017-30/06/2023) - Sjouke Mauw
Funders :
FNR - Fonds National de la Recherche [LU]
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