Detection of Zero-Day Attacks using CNN and LSTM in Networked Autonomous Systems ‘IEEE CNS 23 Poster’ | |
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Author | |
Abstract |
In this paper, we propose a novel approach for detecting zero-day attacks on networked autonomous systems (AS). The proposed approach combines CNN and LSTM algorithms to offer efficient and precise detection of zero-day attacks. We evaluated the proposed approach’s performance against various ML models using a real-world dataset. The experimental results demonstrate the effectiveness of the proposed approach in detecting zero-day attacks in networked AS, achieving better accuracy and detection probability than other ML models. |
Year of Publication |
2023
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Date Published |
oct
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Publisher |
IEEE
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Conference Location |
Orlando, FL, USA
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ISBN Number |
9798350339451
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URL |
https://ieeexplore.ieee.org/document/10288680/
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DOI |
10.1109/CNS59707.2023.10288680
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Google Scholar | BibTeX | DOI |