Digital Forensics in Law Enforcement: A Case Study of LLM-driven Evidence Analysis

Organized by: International Forensic Scientist Awards
Website: forensicscientist.org

13th Edition of Forensic Scientist Awards 28-29 August 2025 | Berlin Germany

In today’s digital age, mobile phones and messaging apps have become central not only to our daily lives but also to criminal investigations. The rise of smartphones has created an explosion of digital evidence—chats, photos, and shared files—that law enforcement agencies must carefully analyze. This mountain of data is both an opportunity and a challenge: it can reveal crucial evidence, but the sheer volume and complexity often slow down investigations.

This is where Large Language Models (LLMs) step in. In our latest case study, we explore how AI-powered models such as GPT-4o, Gemini 1.5, and Claude 3.5 can transform digital forensics by enhancing the analysis of mobile messenger communications.

Why LLMs for Forensics?

LLMs are designed to understand natural language at scale. They can sift through massive volumes of text, detect subtle patterns, and even interpret slang, hidden meanings, and ambiguous word usage—things that often escape conventional forensic tools. With the right prompt engineering, these models can make sense of cryptic conversations that may hide criminal intent.

Our Approach

We conducted experiments using real but anonymized data collected from crime scenes. The models were tasked with:

Identifying hidden meanings in text (e.g., code words or slang).
Contextually interpreting ambiguous language.
Reducing investigative bottlenecks caused by overwhelming data.

To ensure reliable results, we evaluated model performance with key metrics: precision, recall, F1 score, and hallucination rate. This allowed us to measure not just accuracy, but also how often the models generated misleading outputs.

Key Takeaways

Efficiency boost: LLMs can drastically cut down the time investigators spend sorting through irrelevant data.
Context-aware insights: They provide a better understanding of cryptic or coded communications.
Challenges remain: Issues like hallucinations and ethical concerns around AI use must be addressed.

Looking Ahead

LLM-driven digital forensics is still evolving, but its potential to empower law enforcement, strengthen justice, and protect society is undeniable. By blending human expertise with AI precision, investigations can move faster, smarter, and with greater accuracy.

🔗 Learn more and apply at:

https://forensicscientist.org/

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