Contextualized AI for Cyber Defense: An Automated Survey using LLMs
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arXiv
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| Hauptverfasser: | , , , , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866912503391322112 |
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| author | Haryanto, Christoforus Yoga Elvira, Anne Maria Nguyen, Trung Duc Vu, Minh Hieu Hartanto, Yoshiano Lomempow, Emily Arakala, Arathi |
| author_facet | Haryanto, Christoforus Yoga Elvira, Anne Maria Nguyen, Trung Duc Vu, Minh Hieu Hartanto, Yoshiano Lomempow, Emily Arakala, Arathi |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_13524 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Contextualized AI for Cyber Defense: An Automated Survey using LLMs Haryanto, Christoforus Yoga Elvira, Anne Maria Nguyen, Trung Duc Vu, Minh Hieu Hartanto, Yoshiano Lomempow, Emily Arakala, Arathi Cryptography and Security Artificial Intelligence 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. |
| title | Contextualized AI for Cyber Defense: An Automated Survey using LLMs |
| topic | Cryptography and Security Artificial Intelligence |
| url | https://arxiv.org/abs/2409.13524 |