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The article explores cybersecurity challenges in data intensive domains systems, suggesting approaches for AI and ML technologies.
The current stage of development of Russian society is characterized by digital transformation of all its spheres, including economy, science, healthcare, education, culture, etc. One of the areas of such transformation is the widespread use of data intensive domains systems (DID systems), technologies and systems of artificial intelligence (AI) and machine learning (ML). The increasingly widespread use of these systems, their functioning as part of global networks entails new risks of information security, which can negatively affect individuals, groups, organizations, sectors of the economy and society as a whole. Methods of ensuring cybersecurity considering the specifics of these systems and technologies require development. Methodological provisions of the approach to ensuring cybersecurity, reflecting the specifics of the use of AI technologies and systems in DID systems, are defined in the article on the basis of the current regulatory and methodological framework in the field of information security in the country. A general approach to ensuring cybersecurity of business process objects - processing nodes and the DID system as a whole is outlined. Problems and methods for ensuring their protection from these threats are identified. The article examines the problems of ensuring cybersecurity when using AI and ML technologies as part of DID systems to implement functional tasks and issues of using AI and ML technologies to protect against threats of information security breaches.
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Budzko et al. (2025) studied this question.
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