Abstract
The article analyzes business cybersecurity strategies using artificial intelligence technologies, which are currently changing rapidly due to the nature of cyber attacks and the need to find new ways to counter cybersecurity threats. The main purpose of the study is to show how, by introducing artificial intelligence at the micro level, cybersecurity groups can help organizations make more informed business decisions regarding the production and logistics of their products and services, given that cybersecurity and artificial intelligence should work together, create cybersecurity management programs, thereby increasing awareness of the risks associated with cybercrime. Overall, our goal is not only to discuss cybersecurity data science and related techniques, but also to focus on the applicability of cybersecurity to intelligent data-based decision-making to protect systems from cyber attacks. The results of the study are aimed at extracting models of cybersecurity incidents and building an appropriate cybersecurity model in order to (1) make the security system automated and intelligent, and business, having taken steps to mitigate cyber threats, was able to experiment with artificial intelligence and cybersecurity, take on more responsibility, strengthen cooperation, develop a strategy for using artificial intelligence technologies to protect cyberspace; (2) strategically transforming cybersecurity, AI developers should make new changes and make more informed decisions to manage cyber attacks in the business process system; (3) help business leaders determine the timing of investments and the share of the budget for the implementation of AI related to the investment strategy for the development of AI, based on future reports on the evaluation of the effectiveness of AI.
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Nosova, S., Norkina, A., Morozov, N. (2024). Strategies for Business Cybersecurity Using AI Technologies. In: Samsonovich, A.V., Liu, T. (eds) Biologically Inspired Cognitive Architectures 2023. BICA 2023. Studies in Computational Intelligence, vol 1130. Springer, Cham. https://doi.org/10.1007/978-3-031-50381-8_67
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