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    Advancing cyber incident timeline analysis through retrieval-augmented generation and large language models by Loumachi, Fatma Yasmine, Ghanem, Mohamed Chahine, Ferrag, Mohamed Amine

    Published 2025
    “…The proposed framework was tested on synthetic cyber incident events in a controlled environment, with results assessed using DFIR-tailored, context-specific metrics designed to evaluate the framework’s performance, reliability, and robustness, supported by human evaluation to validate the accuracy and reliability of the outcomes. Our findings demonstrate the practical power of LLMs in advancing the automation of cyber-incident timeline analysis, a subfield within DFIR. …”
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