Cybersecurity of systems implementing data intensive domains. Ensuring trust in DID-systems using artificial intelligence and machine learning technologies

The widespread use of systems implementing data intensive domains (DID-systems), artificial intelligence, and machine learning technologies and systems, as well as their operation within global networks, entails new information security risks. Therefore, it is crucial to ensure trust in DID-systems throughout their lifecycle (during design, development, implementation, and maintenance, as well as improvement and development), taking into account the specifics of their use of systems and tools implementing AI and machine learning technologies. Methodological provisions for an approach to ensuring trust in DID-systems throughout their lifecycle, reflecting the specifics of their use of systems and tools implementing AI and machine learning technologies, are defined based on the current regulatory and methodological framework for ensuring trust in the country. General provisions and specific issues of ensuring trust and the ability to trust DID-systems are considered, and the role of adherence to design discipline is demonstrated. The role of cybersecurity, information security, and artificial intelligence systems in ensuring trust and the ability to trust them in an information security system, including one created in accordance with special information protection requirements, is defined. The key principles and mechanisms for achieving a high level of trust are discussed.