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arXiv · 2409.13524

Contextualized AI for Cyber Defense: An Automated Survey using LLMs

Christoforus Yoga Haryanto·Anne Maria Elvira·Trung Duc Nguyen·Minh Hieu Vu·Yoshiano Hartanto·Emily Lomempow·Arathi Arakala
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Abstract

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.

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Christoforus Yoga Haryanto, Anne Maria Elvira, Trung Duc Nguyen, Minh Hieu Vu, Yoshiano Hartanto, Emily Lomempow, Arathi Arakala. 2024-09-20. Contextualized AI for Cyber Defense: An Automated Survey using LLMs. https://doi.org/10.1109/sin63213.2024.10871242

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