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Bimonthly Since 1986 |
ISSN 1004-9037
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Publication Details |
Edited by: Editorial Board of Journal of Data Acquisition and Processing
P.O. Box 2704, Beijing 100190, P.R. China
Sponsored by: Institute of Computing Technology, CAS & China Computer Federation
Undertaken by: Institute of Computing Technology, CAS
Published by: SCIENCE PRESS, BEIJING, CHINA
Distributed by:
China: All Local Post Offices
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05 July-September 2023, Volume 38 Issue 4
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Abstract
Abstract:
It can be challenging to secure the cyber-physical systems (CPS) that power the Internet of Things (IoT), as security measures established for general information and technology operations (IT/OT) may not be effective in a CPS environment. In order to find attacks and techniques created specifically for CPS and more specifically for the control system, this article proposes a two-level common search. This initial phase involves designing a decision tree classifier and new deep learning model for attack detection in a variety of ICS environments. A deep neural network is created for the attack in the second layer. Real data from water pipelines and treatment facilities was used to test the projected model. The outcomes demonstrate that the suggested model performs better than other competing techniques facing comparable challenges.
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