LATIDIA · Ciberseguridad

Informes forenses móviles Android asistidos por LLM basados en evidencia

arXiv: 2610.26946v1Tipo de anuncio: nuevo Resumen: los modelos de lenguaje grandes pueden ayudar a la redacción de informes forenses, pero la salida fluida no garantiza la confiabilidad de las pruebas. Este estudio presenta un marco basado en evidencia para

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arXiv:2610.26946v1 Announce Type: new Abstract: Large language models can assist forensic report drafting, but fluent output does not ensure evidentiary reliability. This study presents an evidence-grounded framework for evaluating LLM-assisted Android forensic reports at the atomic-claim level. Gemini, Llama, and Qwen each generated reports for two controlled cases: a public Android 13 dataset and a physical LG device with a zero-reportable-fact boundary. The six accepted reports were decomposed into 612 claims and evaluated against frozen, human-reviewed authorities through content labeling, citation validation, fact-recall analysis, independent rechecking, and dispute resolution. The final corpus contained 424 supported, 163 unsupported, four contradicted, four overstated or incomplete, and 17 excluded claims. In the public