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AUTOMATED CYBER-RESISTANT SYSTEM IN FOOD ENTERPRISES

Sidorin Sergei Yurievich  (National Research University MAI "Moscow Aviation Institute (National Research University)")

In the modern global space, a digital revolution is currently taking place, the results of which contribute to the implementation and adaptation of digital technologies, machine learning methods and cyber-resistant systems in a manufacturing enterprise. Since the food industry is currently developing under the influence of the constant use of digital technologies, it is advisable to touch upon the topic of developing an automated cyber-resistant system in food enterprises. The aim of the article was to present a review of the literature on cybersecurity in food enterprises, based on a vertical approach, in order to identify the main topics and areas that characterize cybersecurity in the food service industry in the Industry 4.0 paradigm, and to propose a proprietary cyber-resilient system for food enterprises, which was achieved during the research process. The author's concept of an automated cyber-sustainable system in food enterprises was presented, which includes four elements: ICT, artificial intelligence method, supply chain automation and robotization of the production process. Each of the above components works under the influence of the principles of a cyber-sustainable system, which were highlighted in the context of the research: the principle of integration of production processes; use of additional sensors and the Internet of things; machine learning, big data analysis; robotization of production at food enterprises; production planning and management.

Keywords:automated cyber-resistant system, food enterprises, digital revolution, principles, technologies, threat to cybersecurity, cyber attacks and vulnerability
 

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Citation link:
Sidorin S. Y. AUTOMATED CYBER-RESISTANT SYSTEM IN FOOD ENTERPRISES // Современная наука: актуальные проблемы теории и практики. Серия: Естественные и Технические Науки. -2024. -№03. -С. 96-99 DOI 10.37882/2223-2966.2024.03.30
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