Review of Generative AI Methods in Cybersecurity

Yagmur Yigit, William J Buchanan, Madjid G Tehrani,Leandros Maglaras

arxiv(2024)

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摘要
Large language models (LLMs) and generative artificial intelligence (GenAI) constitute paradigm shifts in cybersecurity that present hitherto unseen challenges as well as opportunities. In examining the state-of-the-art application of GenAI in cybersecurity, this work highlights how models like Google's Gemini and ChatGPT-4 potentially enhance security protocols, vulnerability assessment, and threat identification. Our research highlights the significance of a novel approach that employs LLMs to identify and eliminate sophisticated cyber threats. This paper presents a thorough assessment of LLMs' ability to produce important security insights, hence broadening the potential applications of AI-driven cybersecurity solutions. Our findings demonstrate the significance of GenAI in improving digital security. It offers recommendations for further investigations into the intricate relationship between cybersecurity requirements and artificial intelligence's potential.
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