A machine learning-based anomaly detection framework for connected and autonomous vehicles cyber security

Tools

He, Qiyi (2021) A machine learning-based anomaly detection framework for connected and autonomous vehicles cyber security. PhD thesis, University of Nottingham.

[img]
Preview
 PDF (Thesis - as examined) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Available under Licence Creative Commons Attribution.
Download (12MB) | Preview
Item Type: Thesis (University of Nottingham only) (PhD)
Supervisors: Qu, Rong
Keywords: Automated vehicles, Security measures; Machine learning; Anomaly detection (Computer security)
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101 Telecommunication
T Technology > TL Motor vehicles. Aeronautics. Astronautics
Faculties/Schools: UK Campuses > Faculty of Engineering
Item ID: 66838
Depositing User: He, Qiyi
Date Deposited: 08 Dec 2021 04:40
Last Modified: 08 Dec 2021 04:40
URI: https://eprints.nottingham.ac.uk/id/eprint/66838

Actions (Archive Staff Only)

Edit View Edit View