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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.
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Authors (5)
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Fei Li
- Chengdu University Computer Science
-
Haoxi Zhang
- Chengdu University Computer science
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Juan Wang
- Chengdu University Computer Science
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Cesar Sanin
- The University of Newcastle School of Engineering
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- Publication version
- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.1080/01969722.2017.1418788
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- Category:
- Articles
- Type:
- artykuł w czasopiśmie wyróżnionym w JCR
- Published in:
-
CYBERNETICS AND SYSTEMS
no. 49,
pages 412 - 419,
ISSN: 0196-9722 - Language:
- English
- Publication year:
- 2018
- Bibliographic description:
- Li F., Zhang H., Wang J., Sanin C., Szczerbicki E.: Toward Intelligent Vehicle Intrusion Detection Using the Neural Knowledge DNA// CYBERNETICS AND SYSTEMS. -Vol. 49, iss. 5-6 (2018), s.412-419
- DOI:
- Digital Object Identifier (open in new tab) 10.1080/01969722.2017.1418788
- Verified by:
- Gdańsk University of Technology
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