Machine learning and blockchain technologies for cybersecurity in connected vehicles

Ahmad, Jameel;Zia, Muhammad Umer;Naqvi, Ijaz Haider;Chattha, Jawwad Nasar;Butt, Faran Awais;Huang, Tao;Xiang, Wei

Abstract

Future connected and autonomous vehicles (CAVs) must be secured againstcyberattacks for their everyday functions on the road so that safety of passengersand vehicles can be ensured. This article presents a holistic review of cybersecurityattacks on sensors and threats regardingmulti-modal sensor fusion. A compre-hensive review of cyberattacks on intra-vehicle and inter-vehicle communicationsis presented afterward. Besides the analysis of conventional cybersecurity threatsand countermeasures for CAV systems,a detailed review of modern machinelearning, federated learning, and blockchain approach is also conducted to safe-guard CAVs. Machine learning and data mining-aided intrusion detection systemsand other countermeasures dealing with these challenges are elaborated at theend of the related section. In the last section, research challenges and future direc-tions are identified.

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WIREs Data Mining and Knowledge Discovery

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1942-4795

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Wiley

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DOI

10.1002/widm.1515