Spatiotemporal Information Based Intrusion Detection Systems for In-Vehicle Networks

Xiangxue Li; Yue Bao; Xintian Hou

doi:10.1007/978-3-031-28016-0_14

Spatiotemporal Information Based Intrusion Detection Systems for In-Vehicle Networks

Xiangxue Li^*
, Yue Bao
, Xintian Hou

^*此作品的通讯作者

软件工程学院

MatrixElements Technologies
Hou CATARC Software Testing (Tianjin) Co. Ltd

科研成果: 书/报告/会议事项章节 › 章节 › 同行评审

摘要

Since communication security is not a primary concern at the beginning of in-vehicle network protocol design (e.g., controller area network, CAN), it is not a surprise that in-vehicle networks are exposed to numerous security threats. As vehicles are safety-critical, practical and effective steps should be taken to protect drivers and passengers. This chapter describes intrusion detection systems (IDS) on in-vehicle networks for reinforcing CAN security. These IDS mechanisms rely on spatiotemporal information of CAN data frames. Given limited computational power of in-vehicle electronic control units, lightweight IDS is preferred.

源语言	英语
主期刊名	Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems
出版商	Springer International Publishing
页	425-451
页数	27
ISBN（电子版）	9783031280160
ISBN（印刷版）	9783031280153
DOI	https://doi.org/10.1007/978-3-031-28016-0_14
出版状态	已出版 - 1 1月 2023

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10.1007/978-3-031-28016-0_14

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KW - Robustness

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Spatiotemporal Information Based Intrusion Detection Systems for In-Vehicle Networks

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