Since their introduction, researchers have actively explored the applications of LLMs across diverse fields, significantly elevating capabilities. Cybersecurity, traditionally resistant to data-driven solutions and slow to embrace machine learning, stands out as a domain.
This study examines the existing literature, providing a thorough characterization of both defensive and adversarial applications of LLMs within the realm of cybersecurity.
Our review not only surveys and categorizes the current landscape but also identifies critical research gaps. By evaluating both offensive and defensive applications, we aim to provide a holistic understanding of the potential risks and opportunities associated with LLM-driven cybersecurity.
The evolution of generative artificial intelligence, notably large language models LLMs , has influenced most disciplines of science and technology that support content generation in diverse applications Neupane et al.
In education, LLMs support educators in various tasks such as assignment assessment Hsiao et al. In the entertainment industry, LLMs demonstrate competitive performance in generating music captions Deng et al. Automation is introduced into customer service Pandya and Holia, , marketing Gan et al.
