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Automated Reverse Engineering of CAN Protocols

  • Car manufacturers define proprietary protocols to be used inside their vehicular networks, which are kept an industrial secret, therefore impeding independent researchers from extracting information from these networks. This article describes a statistical and a neural network approach that allows reverse engineering proprietary controller area network (CAN)-protocols assuming they were designed using the data base CAN (DBC) file format. The proposed algorithms are tested with CAN traces taken from a real car. We show that our approaches can correctly reverse engineer CAN messages in an automated manner.

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Metadaten
Author:Nils Weiss, Enrico Pozzobon, Jürgen MottokORCiDGND, Václav Matoušek
DOI:https://doi.org/10.14311/NNW.2021.31.015
ISSN:1210-0552
Parent Title (English):Neural Network World
Document Type:Article
Language:English
Year of first Publication:2021
Release Date:2022/03/07
Volume:31
Issue:4
First Page:279
Last Page:295
Institutes:Fakultät Elektro- und Informationstechnik
Fakultät Elektro- und Informationstechnik / Laboratory for Safe and Secure Systems (LAS3)
Begutachtungsstatus:peer-reviewed
research focus:Information und Kommunikation
Licence (German):Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG