Attacks and defences on intelligent connected vehicles: a survey

被引：115

作者：

Dibaei, Mahdi ^{[1
]}

Zheng, Xi ^{[1
]}

Jiang, Kun ^{[2
]}

Abbas, Robert ^{[3
]}

Liu, Shigang ^{[4
]}

Zhang, Yuexin ^{[4
]}

Xiang, Yang ^{[4
]}

Yu, Shui ^{[5
]}

机构：

[1] Macquarie Univ, Dept Comp, Sydney, NSW, Australia

[2] Tsinghua Univ, China State Key Lab Automot Safety & Energy, Beijing, Peoples R China

[3] Macquarie Univ, Sch Engn, Sydney, NSW, Australia

[4] Swinburne Univ Technol, Sch Software & Elect Engn, Hawthorn, Vic, Australia

[5] Univ Technol Sydney, Sch Software, Sydney, NSW, Australia

来源：

DIGITAL COMMUNICATIONS AND NETWORKS | 2020年 / 6卷 / 04期

关键词：

Intelligent vehicles; Vehicular networks; Software vulnerabilities; Deep learning; 3GPP; Software defined; INTRUSION DETECTION SYSTEMS; OF-THE-ART; COMMUNICATIONS PROTOCOL; SECURITY CHALLENGES; STATIC ANALYSIS; PRIVACY; COMMUNICATION; ARCHITECTURE; EFFICIENT; MODEL;

D O I：

10.1016/j.dcan.2020.04.007

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

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.

引用

页码：399 / 421

页数：23

共 197 条

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