Reproduce “Encrypted Federated Search Using Homomorphic Encryption” on OpenResearch
Turn your favorite coding agents into research agents that review literature, develop hypotheses, and run experiments.
Universal app for Apple silicon and Intel. Requires macOS 11 or later.
About this paper
Om Rathod, Aastha Baid, Aswani Kumar Cherukuri
Researchers from Vellore Institute of Technology developed a framework for encrypted federated search, allowing law enforcement agencies to query criminal databases using homomorphic encryption without exposing sensitive information. The system achieved 100% accuracy on small datasets for 'crime type' matching, demonstrating end-to-end confidentiality with an average query latency of approximately 20.5 seconds across three federated databases.
Key insights
- Homomorphic encryption enables end-to-end confidentiality in federated search, allowing computations on sensitive encrypted data without exposure at any stage of the process.
- A hybrid approach combining BFV and CKKS homomorphic encryption schemes effectively handles diverse data types, including both textual and vectorized numerical information, within a unified privacy-preserving framework.
- Implementing homomorphic dot product matching provides a practical method for secure similarity-based record retrieval across distributed databases, despite introducing a computational overhead.
Summary by alphaXiv.
Tip: change arxiv.org to autoarxiv.org in any arXiv abstract link to open the paper here.