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📄 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.