文章摘要
Mahdi Dibaei,Xi Zheng,Kun Jiang,Robert Abbas,Shigang Liu,Yuexin Zhang,Yang Xiang,Shui Yu.[J].重庆邮电大学新办英文刊,2020,(4):399-421
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Attacks and defences on intelligent connected vehicles: a survey
Received: July 13, 2019  Revised: December 21, 2019
DOI:https://doi.org/10.1016/j.dcan.2020.04.007
中文关键词: 
英文关键词: Intelligent vehicles;Vehicular networks;Software vulnerabilities;Deep learning;3GPP;Software defined security
基金项目:
AuthorInstitutionE-mail
Mahdi Dibaei Department of Computing, Macquarie University, Sydney, NSW, Australia dibyimahdi@yahoo.com 
Xi Zheng Department of Computing, Macquarie University, Sydney, NSW, Australia james.zheng@mq.edu.au 
Kun Jiang China State Key Lab of Automotive Safety and Energy, Tsinghua University, Beijing, China jiangkun@tsinghua.edu.cn 
Robert Abbas School of Engineering, Macquarie University, Sydney, NSW, Australia robert.abbas@mq.edu.au 
Shigang Liu School of Software and Electrical Engineering, Swinburne University of Technology, Hawthorn, VIC, Australia shigangliu@swin.edu.au 
Yuexin Zhang School of Software and Electrical Engineering, Swinburne University of Technology, Hawthorn, VIC, Australia yuexinzhang@swin.edu.au 
Yang Xiang School of Software and Electrical Engineering, Swinburne University of Technology, Hawthorn, VIC, Australia yxiang@swin.edu.au 
Shui Yu School of Software, University of Technology Sydney, Australia Shui.Yu@uts.edu.au 
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中文摘要:
      
英文摘要:
      Intelligent vehicles are advancing at a fast speed with the improvement of automation and connectivity, which opens up new possibilities for different cyber-attacks, including in-vehicle attacks (e.g., hijacking attacks) and vehicle-to-everything communicationattacks (e.g., data theft). These problems are becoming increasingly serious with the development of 4G LTE and 5G communication technologies. Although many efforts are made to improve the resilience to cyber attacks, there are still many unsolved challenges. This paper first identifies some major security attacks on intelligent connected vehicles. Then, we investigate and summarize the available defences against these attacks and classify them into four categories: cryptography, network security, software vulnerability detection, and malware detection. Remaining challenges and future directions for preventing attacks on intelligent vehicle systems have been discussed as well.