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Defensible AI-Assisted DFIR: Evidence Grounding, Triage, and Timeline Reconstruction Without Vendor Lock-In
Abstract Proposal: Modern intrusions leverage automation and adaptive tactics that challenge traditional DFIR. This session presents a case study demonstrating an AI-assisted investigation workflow for evidence-grounded analysis and defensible reporting. Attendees will learn: (1) how to validate AI outputs against raw artefacts (logs, processes, network traces), (2) how to triage and correlate multi-source evidence, and (3) how to reconstruct verifiable timelines while preserving chain of custody and auditability.
