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arXiv The work proposes ChatIDS, which anonymizes alerts from a network-based intrusion detection system (IDS) and passes them to a large language model (implemented with ChatGPT/gpt-3.5-turbo) to produce plain-language explanations and suggested countermeasures for home users without cybersecurity expertise, then assesses feasibility on 20 typical alerts and compiles open issues with interdisciplinary AI experts.
The work proposes ChatIDS, which anonymizes alerts from a network-based intrusion detection system (IDS) and passes them to a large language model (implemented with ChatGPT/gpt-3.5-turbo) to produce plain-language explanations and suggested countermeasures for home users without cybersecurity expertise, then assesses feasibility on 20 typical alerts and compiles open issues with interdisciplinary AI experts.
The work proposes ChatIDS, which anonymizes alerts from a network-based intrusion detection system (IDS) and passes them to a large language model (implemented with ChatGPT/gpt-3.5-turbo) to produce plain-language explanations and suggested countermeasures for home users without cybersecurity expertise, then assesses feasibility on 20 typical alerts and compiles open issues with interdisciplinary AI experts.
The work proposes ChatIDS, which anonymizes alerts from a network-based intrusion detection system (IDS) and passes them to a large language model (implemented with ChatGPT/gpt-3.5-turbo) to produce plain-language explanations and suggested countermeasures for home users without cybersecurity expertise, then assesses feasibility on 20 typical alerts and compiles open issues with interdisciplinary AI experts.