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Cybersecurity for autonomous vehicles: Review of attacks and defense

Authors
Kim, KyounggonKim, Jun SeokJeong, SeonghoonPark, Jo-HeeKim, Huy Kang
Issue Date
4월-2021
Publisher
ELSEVIER ADVANCED TECHNOLOGY
Keywords
Smart city; Smart mobility; Autonomous vehicle artificial; intelligence security survey
Citation
COMPUTERS & SECURITY, v.103
Indexed
SCIE
SCOPUS
Journal Title
COMPUTERS & SECURITY
Volume
103
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/128305
DOI
10.1016/j.cose.2020.102150
ISSN
0167-4048
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. (c) 2021 Elsevier Ltd. All rights reserved.
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