Enhancing Digital Forensics Evidence Analysis with Large Language Models

Enhancing Digital Forensics Evidence Analysis with Large Language Models

연구 분야: Analysis

학회: KDD '25: Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2

In an era where justice and accountability increasingly depend on digital evidence, Large Language Models (LLMs) offer transformative potential for digital forensics. This three-hour Hands-on tutorial explores how LLMs can automate investigations, reveal hidden insights, and enhance evidence analysis. Through real-world case studies, interactive exercises, and hands-on labs, participants will learn to leverage LLMs for tasks such as entity identification, evidence processing, and knowledge graph reconstruction. Designed for professionals, researchers, and students, this collaborative learning experience equips attendees with practical skills to innovate in digital forensics. As LLMs reshape the field, this tutorial underscores their role in improving justice outcomes, strengthening accountability, and advancing the future of digital investigations.