Contextualized AI for Cyber Defense: An Automated Survey using LLMs
<|reference_start|>Contextualized AI for Cyber Defense: An Automated Survey using LLMs: 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.<|reference_end|>
@article{haryanto2024contextualized,
    title={Contextualized AI for Cyber Defense: An Automated Survey using LLMs},
    author={Christoforus Yoga Haryanto, Anne Maria Elvira, Trung Duc Nguyen, Minh
  Hieu Vu, Yoshiano Hartanto, Emily Lomempow, Arathi Arakala},
    journal={arXiv preprint arXiv:2409.13524},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.13524},
    primaryClass={cs.CR cs.AI}
}