Source Identification from In-Vehicle CAN-FD Signaling: What Can We Expect?

Yucheng Liu, Xiangxue Li*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Controller Area Network (CAN) is significantly deployed in various industrial applications (including current in-vehicle network) due to its high performance and reliability. Controller area network with flexible data rate (CAN-FD) is supposed to be the next generation of in-vehicle network to dispose of CAN limitations of data payload size and bandwidth. The paper explores for the first time Electronic Control Unit (ECU) identification on in-vehicle CAN-FD network from bus signaling and the contributions are four-fold. Technically, we discuss the factors that might affect ECU recognition (e.g., CAN-FD controller, CAN-FD transceiver, and voltage regulator) and look into the signal ringing and its intensity where dominant states along with rising edges (from recessive to dominant states) suffice to fingerprint the ECUs. We can thereby design ECU identification scheme on in-vehicle CAN-FD network.For a given network topology (in terms of the stub length and the number of ECUs), we execute CAN-FD and CAN separately and one can expect considerable performance for the two kinds of protocols by using any signal characteristics (rising edges, dominant states, falling edges, and recessive states). In particular, the recognition rates by dominant states and rising edges of signals outperform significantly those by any other combinations of signal characteristics.As a respond to the possible transition mechanism from CAN to CAN-FD, we also allow a hybrid topology of CAN and CAN-FD, namely, there exist on the network ECUs sending purely CAN frames, ECUs sending purely CAN-FD frames, and ECUs sending both CAN and CAN-FD frames, and our suggestion on dominant states and rising edges shows robustness to source identification as expected. This shows convincing evidence on the universal applicability of our approach to forthcoming real vehicles set up by CAN-FD network.The proposed approach can be easily extended to intrusion detection against attacks not only initiated by external devices but also internal devices. We hope our results could be used as a step forward and a guidance on securing the commercialization and batch production of in-vehicle CAN-FD network in the near future.

Original languageEnglish
Title of host publicationInformation and Communications Security - 23rd International Conference, ICICS 2021, Proceedings
EditorsDebin Gao, Qi Li, Xiaohong Guan, Xiaofeng Liao
PublisherSpringer Science and Business Media Deutschland GmbH
Pages204-223
Number of pages20
ISBN (Print)9783030868895
DOIs
StatePublished - 2021
Event23rd International Conference on Information and Communications Security, ICICS 2021 - Chongqing, China
Duration: 19 Nov 202121 Nov 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12918 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference23rd International Conference on Information and Communications Security, ICICS 2021
Country/TerritoryChina
CityChongqing
Period19/11/2121/11/21

Keywords

  • CAN-FD
  • Controller Area Network
  • ECU identification

Fingerprint

Dive into the research topics of 'Source Identification from In-Vehicle CAN-FD Signaling: What Can We Expect?'. Together they form a unique fingerprint.

Cite this