A Review of Anomalous Behavior Detection in Internet of Vehicles

Jun Ren

doi:10.62051/ijcsit.v3n1.11

Authors

Jun Ren

DOI:

https://doi.org/10.62051/ijcsit.v3n1.11

Keywords:

Internet of Vehicles, Abnormal Behavior Detection, Deep Learning

Abstract

The intelligent transportation system with the Internet of Vehicles as its core is gradually penetrating into the lives of urban residents, but it has also exposed security threats such as remote control of vehicles and leakage of personal information of car owners. Compared to the security issues at the level of vehicle end devices and vehicle networking service platforms, the article focuses on the security issues of abnormal behavior in vehicle networking. Based on this, the article reviews the relevant research on abnormal behavior detection mechanisms in the Internet of Vehicles environment in recent years. Firstly, the definition of abnormal behavior was analyzed, and the basic framework for detecting abnormal behavior was provided; Then, the classification of abnormal behavior detection mechanisms was discussed from three aspects: deep learning based abnormal behavior detection, spatiotemporal fusion based abnormal behavior detection, and visual based abnormal behavior detection; Finally, the unresolved technical issues and future research trends in the current abnormal behavior detection mechanism for the Internet of Vehicles were summarized.

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