Machine Learning based intrusion detection systems for connected autonomous vehicles: A survey-Reference-Cited by-同舟云学术

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Machine Learning based intrusion detection systems for connected autonomous vehicles: A survey

Published:2023-07-10 Issue:5 Volume:16 Page:2153-2185
ISSN:1936-6442
Container-title:Peer-to-Peer Networking and Applications
language:en
Short-container-title:Peer-to-Peer Netw. Appl.

Author:

Nagarajan Jay,Mansourian Pegah,Shahid Muhammad Anwar,Jaekel Arunita,Saini Ikjot,Zhang Ning,Kneppers Marc

Funder

Mitacs Accelerate Program

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Software

Link

https://link.springer.com/content/pdf/10.1007/s12083-023-01508-7.pdf

Reference166 articles.

1. Ye X, Zhou J, Li Y, Cao M, Chen D, Qin Z (2021) A location privacy protection scheme for convoy driving in autonomous driving era. Peer Peer Netw Appl 14(3):1388–1400

2. Yang Q, Fu S, Wang H, Fang H (2021) Machine-learning-enabled cooperative perception for connected autonomous vehicles: challenges and opportunities. IEEE Netw 35(3):96–101

3. Taherkhani N, Pierre S (2016) Centralized and localized data congestion control strategy for vehicular ad hoc networks using a machine learning clustering algorithm. IEEE Trans Intell Transp Syst 17(11):3275–3285

4. Reebadiya D, Rathod T, Gupta R, Tanwar S, Kumar N (2021) Blockchain-based secure and intelligent sensing scheme for autonomous vehicles activity tracking beyond 5G networks. Peer Peer Netw Appl 14(5):2757–2774

5. Sun X, Yu FR, Zhang P (2021) A survey on cyber-security of connected and autonomous vehicles (CAVS). IEEE Trans Intell Transp Syst

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