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Two-Party Privacy-Preserving Set Intersection with FHE.

Yunlu Cai1, Chunming Tang1,2, Qiuxia Xu3

  • 1School of Mathematics and Information Science, Guangzhou University, Guangzhou 510006, China.

Entropy (Basel, Switzerland)
|December 3, 2020
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We developed new private set intersection protocols using fully homomorphic encryption. These methods enable secure data intersection, even when outsourced to cloud providers, protecting sensitive information.

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fully homomorphic encryptionprivacy-preservingprivate set intersectionsecure multiparty computation

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Area of Science:

  • Cryptography
  • Computer Science
  • Information Security

Background:

  • Private Set Intersection (PSI) enables secure computation of common elements between two datasets.
  • Existing PSI protocols often face scalability challenges or reveal information beyond the intersection.

Purpose of the Study:

  • To propose novel, secure, and efficient Private Set Intersection protocols.
  • To enhance data privacy in collaborative computing scenarios, including cloud outsourcing.

Main Methods:

  • Developed a PSI protocol leveraging Shuhong Gao's fully homomorphic encryption (FHE) scheme.
  • Introduced a variant combining Bloom filters and FHE for improved efficiency, with complexity independent of client set size.
  • Security analysis conducted under the semi-honest model, relying on hardness of Learning With Errors (LWE) and Ring LWE problems.

Main Results:

  • Demonstrated the security of the proposed PSI protocols in the semi-honest model.
  • The Bloom filter-based variant offers computational efficiency independent of the client's dataset size.
  • Enabled secure outsourcing of PSI computations to cloud environments with malicious adversaries.

Conclusions:

  • The novel PSI protocols offer enhanced security and efficiency for private data analysis.
  • The FHE and Bloom filter-based approach provides a scalable solution for private set intersection.
  • Secure outsourcing of PSI to the cloud is feasible, protecting sensitive data from malicious cloud providers.