Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/61855
Title: Toward Intelligent Vehicle Intrusion Detection Using the Neural Knowledge DNA
Contributor(s): Li, Fei (author); Zhang, Haoxi (author); Wang, Juan (author); Liu, Yong (author); Gao, Lulu (author); Xu, Xiang (author); Sanin, Cesar  (author)orcid ; Szczerbicki, Edward (author)
Publication Date: 2018
Early Online Version: 2018-02-12
DOI: 10.1080/01969722.2017.1418788
Handle Link: https://hdl.handle.net/1959.11/61855
Abstract: 

In this paper, we propose a novel intrusion detection approach using past driving experience and the neural knowledge DNA for in-vehicle information system security. The neural knowledge DNA is a novel knowledge representation method designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing systems. We examine our approach for classifying malicious vehicle control commands based on learning from past valid driving behavior data on a simulator.

Publication Type: Journal Article
Source of Publication: Cybernetics and Systems, 49(5-6), p. 412-419
Publisher: Taylor & Francis Inc
Place of Publication: United States of America
ISSN: 1087-6553
0196-9722
Fields of Research (FoR) 2020: 4602 Artificial intelligence
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Science and Technology

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