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Beyond the Hype: A Comparative Case Study of the Impact of Artificial Intelligence and Machine Learning on Cybersecurity
De Blasi, Stefano ; Kilroy, Walt (vedoucí práce) ; Kaczmarski, Marcin (oponent) ; Špelda, Petr (oponent)
Artificial intelligence (AI) and machine learning (ML) are largely touted as the silver bullet for the shortcomings of cybersecurity. Driven by the latest achievements of machine learning in fields such as finance, healthcare, and commerce, security researchers and marketing strategists have ubiquitously employed AI and ML as buzzwords to rise the competitiveness of their products. This study aims at verifying the substance of such claims by assessing the extent of the impact of AI and ML products in the cybersecurity practice. To provide a reliable and valid assessment of this phenomenon, the researcher developed an original framework based on the comparison of three security disciplines: cyber threat intelligence, endpoint protection, and incident response. Each discipline is further analysed in terms of the improvements brought by artificial intelligence and machine learning products to the speed, accuracy, and innovation of their security operations. These results indicate that the impact of AI and ML products in cybersecurity is limited to environments characterised by vast amounts of healthy datasets and a partially limited range of options. On the other hand, the cyberspace is extremely variable and volatile and, thus, makes artificial intelligence and machine learning products severely...
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