In-Vehicle Communication Cyber Security: Challenges and Solutions

Rajkumar Singh Rathore, Chaminda Hewage, Omprakash Kaiwartya*, Jaime Lloret

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

52 Citations (Scopus)

Abstract

In-vehicle communication has become an integral part of today’s driving environment considering the growing add-ons of sensor-centric communication and computing devices inside a vehicle for a range of purposes including vehicle monitoring, physical wiring reduction, and driving efficiency. However, related literature on cyber security for in-vehicle communication systems is still lacking potential dedicated solutions for in-vehicle cyber risks. Existing solutions are mainly relying on protocol-specific security techniques and lacking an overall security framework for in-vehicle communication. In this context, this paper critically explores the literature on cyber security for in-vehicle communication focusing on technical architecture, methodologies, challenges, and possible solutions. In-vehicle communication network architecture is presented considering key components, interfaces, and related technologies. The protocols for in-vehicle communication have been classified based on their characteristics, and usage type. Security solutions for in-vehicle communication have been critically reviewed considering machine learning, cryptography, and port-centric techniques. A multi-layer secure framework is also developed as a protocol and use case-independent in-vehicle communication solution. Finally, open challenges and future dimensions of research for in-vehicle communication cyber security are highlighted as observations and recommendations.

Original languageEnglish
Article number6679
JournalSensors
Volume22
Issue number17
DOIs
Publication statusPublished - 3 Sept 2022

Keywords

  • controller area network (CAN)
  • cryptography
  • cyber attacks
  • cyber security
  • in-vehicle network
  • intrusion detection system
  • machine learning
  • smart intelligent vehicles

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