Autors: Trifonov, R. I., Sabev E., Pavlova, G. V., Raynova, K. S.
Title: Analysis of Deep Learning Methods for Cybersecurity in Industry 4.0
Keywords:

Abstract: Nowadays the use of Artificial Intelligence (AI) around the globe is constantly growing. These processes were accelerated even more due to the COVID-19 pandemic. In the cybersecurity realm, the real implementations of AI solutions are also constantly growing. For some enterprises, AI is considered more as a risk for overall cybersecurity while others see AI as the way forward to achieve cyber resilience. That kind of uncertainty points out that cybersecurity leaders are still not united around AI and do not fully understand the effects of utilizing it. That lack of understanding is emphasizing again the need for more research into AI for cybersecurity and in addition to that the urgency of attracting young talent to the cybersecurity career path. On the other hand, cyber threat actors are getting more and more sophisticated and may already be on the way to integrating AI into their future attacks. In this paper, we are analyzing the artificial intelligence methods for cybersecurity in Industry 4.0. In addition, we detail the challenges, motivations, and pre-conditions to be taken into consideration when using these AI methods for improving overall cybersecurity in Industry 4.0.

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Issue

AIP Conference Proceedings, vol. 3084, 2024, , https://doi.org/10.1063/5.0193712

Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus