TY - JOUR
T1 - Cybersecurity for autonomous vehicles
T2 - Review of attacks and defense
AU - Kim, Kyounggon
AU - Kim, Jun Seok
AU - Jeong, Seonghoon
AU - Park, Jo Hee
AU - Kim, Huy Kang
N1 - Funding Information:
The study was funded by Institute for Information and communications Technology Promotion (Grant No. 2020-0-00374, Development of Security Primitives for Unmanned Vehicles). Also, this study was supported by a Korea University Grant.
Publisher Copyright:
© 2021
PY - 2021/4
Y1 - 2021/4
N2 - 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.
AB - 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.
KW - Autonomous vehicle artificial intelligence security survey
KW - Smart city
KW - Smart mobility
UR - http://www.scopus.com/inward/record.url?scp=85099436265&partnerID=8YFLogxK
U2 - 10.1016/j.cose.2020.102150
DO - 10.1016/j.cose.2020.102150
M3 - Review article
AN - SCOPUS:85099436265
SN - 0167-4048
VL - 103
JO - Computers and Security
JF - Computers and Security
M1 - 102150
ER -