EFFECTIVENESS OF ARTIFICIAL INTELLIGENCE ALGORITHMS IN CYBERSECURITY
DOI:
https://doi.org/10.5281/zenodo.15475157Keywords:
Artificial intelligence, cybersecurity, machine learning, anomaly detection, deepfake, adversarial attack, information security.Abstract
This article provides a scientific analysis of the application of artificial intelligence algorithms in the field of cybersecurity, their effectiveness, and practical results. It analyzes how key AI technologies such as machine learning, in-depth learning, and anomaly detection work in security systems. In the process of ensuring cybersecurity, the functions of AI, such as machine learning, detection of unusual situations, and automated decision-making, are highlighted. Risks that can arise through artificial intelligence are also considered - in particular, such aspects as deepfake technologies, algorithmic errors, ethical problems, and counterattacks.
References
Smith, J. (2021). AI in Cybersecurity: Threat Detection and Prevention. CyberTech Journal.
Chen, L., Wu, X., & Zhang, Y. (2022). Deep Learning Approaches to Cybersecurity. IEEE Transactions on Neural Networks.
Darktrace. (2021). Case Studies. https://www.darktrace.com
IBM Security. (2023). Watson for Cyber Security. IBM White Papers.
O'G'Li, U. Z. B., O'G, T. Y. I. К., & Muzaffarovna, A. N. (2019). Problems encountered in learning English for specific purposes. Вопросы науки и образования, (3 (47)), 139-142.
Google Chronicle. (2022). AI-driven Threat Intelligence. Google Cloud Blog
