Contextualized AI for Cyber Defense: An Automated Survey using LLMs
It addresses the problem of enhancing cyber defense capabilities for researchers and practitioners, but it is incremental as a survey.
This paper surveys the use of contextualized AI in cyber defense, identifying research growth from 2015 to 2024 and highlighting gaps in trust and governance.
This paper surveys the potential of contextualized AI in enhancing cyber defense capabilities, revealing significant research growth from 2015 to 2024. We identify a focus on robustness, reliability, and integration methods, while noting gaps in organizational trust and governance frameworks. Our study employs two LLM-assisted literature survey methodologies: (A) ChatGPT 4 for exploration, and (B) Gemma 2:9b for filtering with Claude 3.5 Sonnet for full-text analysis. We discuss the effectiveness and challenges of using LLMs in academic research, providing insights for future researchers.