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arxiv_crypto 95% Match Research Paper Cryptographers,Security engineers,Privacy researchers,Developers of secure systems 1 month ago

Authenticated Private Set Intersection: A Merkle Tree-Based Approach for Enhancing Data Integrity

ai-safety › privacy
📄 Abstract

Abstract: Private Set Intersection (PSI) enables secure computation of set intersections while preserving participant privacy, standard PSI existing protocols remain vulnerable to data integrity attacks allowing malicious participants to extract additional intersection information or mislead other parties. In this paper, we propose the definition of data integrity in PSI and construct two authenticated PSI schemes by integrating Merkle Trees with state-of-the-art two-party volePSI and multi-party mPSI protocols. The resulting two-party authenticated PSI achieves communication complexity $\mathcal{O}(n \lambda+n \log n)$, aligning with the best-known unauthenticated PSI schemes, while the multi-party construction is $\mathcal{O}(n \kappa+n \log n)$ which introduces additional overhead due to Merkle tree inclusion proofs. Due to the incorporation of integrity verification, our authenticated schemes incur higher costs compared to state-of-the-art unauthenticated schemes. We also provide efficient implementations of our protocols and discuss potential improvements, including alternative authentication blocks.

Key Contributions

This paper introduces the concept of data integrity in Private Set Intersection (PSI) and proposes two authenticated PSI schemes by integrating Merkle Trees with existing two-party and multi-party PSI protocols. These schemes enhance security against data integrity attacks while maintaining competitive communication complexity.

Business Value

Enables more secure and trustworthy data sharing and collaborative analysis between parties, crucial for applications like fraud detection, threat intelligence sharing, and privacy-preserving analytics.