Cybersecurity for autonomous vehicles: Review of attacks and defense. Issue 103 (April 2021)

• Record Type: Journal Article
• Authors: Kim, Kyounggon; Kim, Jun Seok; Jeong, Seonghoon; Park, Jo-Hee; Kim, Huy Kang
• Is Part Of: Computers & security. Issue 103(2021)
• Publication Date: 2021-04
• Subjects: Smart city -- Smart mobility -- Autonomous vehicle artificial intelligence security survey; Computer security -- Periodicals; Electronic data processing departments -- Security measures -- Periodicals; 005.805
• DOI: 10.1016/j.cose.2020.102150
• Languages: English
• ISSNs: 0167-4048

Abstract

Highlights: Research conducted for attacks and defenses against autonomous cars is organized in chronological order, indicating the technologies that have been used over time concisely. 151 papers from 2008 to 2019 on attacks and defenses against autonomous vehicles are summarized. Through a comprehensive investigation of attacks on autonomous vehicles, it can be observed that, in the future, attacks on autonomous vehicles will increasingly target vehicle-to-everything (V2X) technology related to communication rather than other simpler elements of the vehicles. The research trend in autonomous vehicle security indicated that artificial intelligence with big data has been used to defend autonomous vehicle attacks. Abstract: As technology has evolved, cities have become increasingly smart. Smart mobility is a crucial element in smart cities, and autonomous vehicles are an essential part of smart mobility. However, vulnerabilities in autonomous vehicles can be damaging to quality of life and human safety. For this reason, many security researchers have studied attacks and defenses for autonomous vehicles. However, there has not been systematic research on attacks and defenses for autonomous vehicles. In this survey, we analyzed previously conducted attack and defense studies described in 151 papers from 2008 to 2019 for a systematic and comprehensive investigation of autonomous vehicles. We classified autonomous attacks into the three categories of autonomous control system, autonomous driving systems components, and vehicle-to-everything communications. Defense against such attacks was classified into security architecture, intrusion detection, and anomaly detection. Due to the development of big data and communication technologies, techniques for detecting abnormalities using artificial intelligence and machine learning are gradually being developed. Lastly, we provide implications based on our systemic survey that future research on autonomous attacks and defenses is strongly combined with artificial intelligence and major component of smart cities.