Question 1

What problem does the RAG-LangChain fusion system target in digital forensics?

Accepted Answer

It targets traditional tool inefficiency and large-model limitations in adapting to domain-specific queries and processing sensitive local data for real-time, personalized retrieval.

Question 2

How does the proposed assistant handle multimodal electronic evidence securely on-premise?

Accepted Answer

It uses RAG to retrieve text, images, and documents from a local vector database, while LangChain provides a modular pipeline with secure control. Multi-layer encryption supports on-premise deployment and judicial privacy requirements.

Question 3

What performance improvements are reported compared with conventional models?

Accepted Answer

Experiments on 30 specialized tasks report advantages in accuracy, counterfactual robustness, practicality, and robustness, with an overall performance about 7.8% higher than baseline models such as DeepSeek-V3.