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Harnessing the Power of Large Language Models for Cybersecurity: Applications, Challenges, and Future Directions
Abstract
The LLMs not only have changed the overall nature of NPL but have also helped a lot in setting standards in cyber security. Within the confines of this review, the authors discuss the benefits, progressions, difficulties, as well as the future paths aimed to be taken in the cybersecurity field of LLMs. They delve into how LLMs help companies process unstructured textual data for text dangers detections, vulnerability assessments, and incident responses. In addition, they investigate the ethical and societal consequences of using LLMs for cybersecurity, facing challenges like algorithmic bias, privacy, and data safety. Besides that, they find that critical research questions in the crossroads of LLMs and cybersecurity language include unique assessing techniques and the improvement of algorithms to clarify the information. Through the development of many-faceted interdisciplinary cooperation and ethics-based considerations, we can maximize the opportunities LLMs present in the cyber world and build a more resilient and secure environment for everyone.
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