In-Vehicle Communication Cyber Security: Challenges and Solutions

被引:42
作者
Rathore, Rajkumar Singh [1 ]
Hewage, Chaminda [1 ]
Kaiwartya, Omprakash [2 ]
Lloret, Jaime [3 ]
机构
[1] Cardiff Metropolitan Univ, Cardiff Sch Technol, Dept Comp Sci, Cardiff Llandaff Campus, Cardiff CF5 2YB, Wales
[2] Nottingham Trent Univ, Dept Comp Sci, Clifton Campus, Nottingham NG11 8NS, England
[3] Univ Politecn Valencia, Dept Commun, E-46022 Valencia, Spain
关键词
machine learning; cryptography; cyber attacks; cyber security; intrusion detection system; smart intelligent vehicles; in-vehicle network; controller area network (CAN); CONTROLLER AREA NETWORK; INTRUSION DETECTION SYSTEM; ANOMALY DETECTION; FAULT-DIAGNOSIS; AUTHENTICATION; INTERNET; SCHEME; ARCHITECTURE; EFFICIENT; IDENTIFIER;
D O I
10.3390/s22176679
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
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.
引用
收藏
页数:33
相关论文
共 50 条
  • [21] Cyber physical systems security: Analysis, challenges and solutions
    Ashibani, Yosef
    Mahmoud, Qusay H.
    COMPUTERS & SECURITY, 2017, 68 : 81 - 97
  • [22] INVESTIGATION ON CYBER-ATTACKS AGAINST IN-VEHICLE NETWORK
    Kumar, S. Vishnu
    Mary, G. Aloy Anuja
    Suresh, P.
    Uthirasamy, R.
    2021 7TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENERGY SYSTEMS (ICEES), 2021, : 305 - 311
  • [23] Enhancing Security in Vehicle-to-Vehicle Communication: A Comprehensive Review of Protocols and Techniques
    Muslam, Muhana Magboul Ali
    VEHICLES, 2024, 6 (01): : 450 - 467
  • [24] Electric Vehicle Charging Station: Cyber Security Challenges and Perspective
    Pourmirza, Zoya
    Walker, Sara
    2021 THE 9TH IEEE INTERNATIONAL CONFERENCE ON SMART ENERGY GRID ENGINEERING (SEGE 2021), 2021, : 111 - 116
  • [25] A Kohonen SOM Architecture for Intrusion Detection on In-Vehicle Communication Networks
    Santa Barletta, Vita
    Caivano, Danilo
    Nannavecchia, Antonella
    Scalera, Michele
    APPLIED SCIENCES-BASEL, 2020, 10 (15):
  • [26] Supply Chain 4.0: A Survey of Cyber Security Challenges, Solutions and Future Directions
    Sobb, Theresa
    Turnbull, Benjamin
    Moustafa, Nour
    ELECTRONICS, 2020, 9 (11) : 1 - 31
  • [27] A Novel Architecture for an Intrusion Detection System Utilizing Cross-Check Filters for In-Vehicle Networks
    Im, Hyungchul
    Lee, Donghyeon
    Lee, Seongsoo
    SENSORS, 2024, 24 (09)
  • [28] IntruDTree: A Machine Learning Based Cyber Security Intrusion Detection Model
    Sarker, Iqbal H.
    Abushark, Yoosef B.
    Alsolami, Fawaz
    Khan, Asif Irshad
    SYMMETRY-BASEL, 2020, 12 (05):
  • [29] Review of In-Vehicle Optical Fiber Communication Technology
    Wang, Wenwei
    Yu, Shiyao
    Cao, Wanke
    Guo, Kaidi
    AUTOMOTIVE INNOVATION, 2022, 5 (03) : 272 - 284
  • [30] In-vehicle network intrusion detection systems: a systematic survey of deep learning-based approaches
    Luo, Feng
    Wang, Jiajia
    Zhang, Xuan
    Jiang, Yifan
    Li, Zhihao
    Luo, Cheng
    PEERJ COMPUTER SCIENCE, 2023, 9