IntelliCAN: Attack-resilient Controller Area Network (CAN) for secure automobiles

Mohammad Raashid Ansari, Shucheng Yu, Qiaoyan Yu

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

11 Scopus citations

Abstract

Controller Area Network (CAN) is the main bus network that connects electronic control units in automobiles. Although CAN protocols have been revised to improve the vehicle safety, the security weaknesses of CAN have not been fully addressed. Security threats on automobiles might be from external wireless communication or from internal malicious CAN nodes mounted on the CAN bus. Despite of various threat sources, the security weakness of CAN is the root of security problems. Due to the limited computation power and storage capacity on each CAN node, there is a lack of hardware-efficient protection methods for the CAN system without losing the compatibility to CAN protocols. To save the cost and maintain the compatibility, we propose to exploit the built-in CAN fault confinement mechanism to detect the masquerade attacks originated from the malicious CAN devices on the CAN bus. Simulation results show that our method achieves the attack misdetection rate at the order of 10-5 and reduces the encryption latency by up to 68% over the complete frame encryption method.

Original languageEnglish
Title of host publicationProceedings of the 2015 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems, DFTS 2015
Pages233-236
Number of pages4
ISBN (Electronic)9781509003129
DOIs
StatePublished - 2 Nov 2015
Event28th IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems, DFTS 2015 - Amherst, United States
Duration: 12 Oct 201514 Oct 2015

Publication series

NameProceedings of the 2015 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems, DFTS 2015

Conference

Conference28th IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems, DFTS 2015
Country/TerritoryUnited States
CityAmherst
Period12/10/1514/10/15

Keywords

  • Automobile
  • controller area network(CAN)
  • error detection
  • hardware security
  • masquerade attack
  • security

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