PRIVERA: A Privacy-Preserving, Explainable Retrieval Assistant

PRIVERA, a privacy-preserving, explainable retrieval assistant.

PRIVERA, a privacy-preserving, explainable retrieval assistant. This reference project walks through the whole job, from the problem and the design to the build and the evaluation, so that a developer can study how it works, run it and extend it.

It suits learners who want practical security experience: understanding the threat, building the defence or detector, testing it against realistic attacks and reporting the results.

The main parts are explanations of each result (feature importance or visual evidence), a conversational interface, security and privacy controls such as encryption and access control, a realistic threat model, and the detection or protection mechanism itself. The reference build uses LangChain, FAISS, SHAP, Python, and scikit-learn, with a clear project structure, setup instructions and sample data so that it can be run and extended.