DP-PSI: Private and Secure Set Intersection
Jian Du, Tianxi Ji, Jamie Cui, Lei Zhang, Yufei Lu, Pu, Duan

TL;DR
This paper introduces DP-PSI, a novel private set intersection protocol combining differential privacy and secure computation to prevent signaling out attacks, ensuring strong security and privacy in joint data analysis.
Contribution
The paper proposes a new privacy model, DP-PSI, that enhances security in PSI by preventing signaling out attacks while maintaining cryptographic privacy guarantees.
Findings
DP-PSI effectively prevents signaling out attacks.
The protocol balances privacy, security, and practical usability.
It aligns with GDPR's privacy requirements.
Abstract
One way to classify private set intersection (PSI) for secure 2-party computation is whether the intersection is (a) revealed to both parties or (b) hidden from both parties while only the computing function of the matched payload is exposed. Both aim to provide cryptographic security while avoiding exposing the unmatched elements of the other. They may, however, be insufficient to achieve security and privacy in one practical scenario: when the intersection is required and the information leaked through the function's output must be considered for legal, ethical, and competitive reasons. Two parties, such as the advertiser and the ads supplier, hold sets of users for PSI computation, for example, to reveal common users to the ads supplier in joint marketing applications. In addition to the security guarantees required by standard PSIs to secure unmatched elements, neither party is…
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Taxonomy
TopicsPrivacy-Preserving Technologies in Data · Cryptography and Data Security · Blockchain Technology Applications and Security
