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Scaling Private Set Intersection to Billion-Element Sets

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Book cover Financial Cryptography and Data Security (FC 2014)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 8437))

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Abstract

We examine the feasibility of private set intersection (PSI) over massive datasets. PSI, which allows two parties to find the intersection of their sets without revealing them to each other, has numerous applications including to privacy-preserving data mining, location-based services and genomic computations. Unfortunately, the most efficient constructions only scale to sets containing a few thousand elements—even in the semi-honest model and over a LAN.

In this work, we design PSI protocols in the server-aided setting, where the parties have access to a single untrusted server that makes its computational resources available as a service. We show that by exploiting the server-aided model and by carefully optimizing and parallelizing our implementations, PSI is feasible for billion-element sets even while communicating over the Internet. As far as we know, ours is the first attempt to scale PSI to billion-element sets which represents an increase of five orders of magnitude over previous work.

Our protocols are secure in several adversarial models including against a semi-honest, covert and malicious server; and address a range of security and privacy concerns including fairness and the leakage of the intersection size. Our protocols also yield efficient server-aided private equality-testing (PET) with stronger security guarantees than prior work.

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Notes

  1. 1.

    An alternative approach considered in the PSI literature is the use of tamper-proof hardware in the design of private set intersection [30, 38]. This approach allows for better efficiency and hence more scalable protocols. Token-based PSI makes different and incomparable trust assumptions compared to server-aided MPC, and does not seem suitable for settings that involve a cloud service.

  2. 2.

    Due to space limitations we had to omit our security definitions and proofs. The full version of this work with definitions and proofs is available on request.

  3. 3.

    The full version is available upon request.

  4. 4.

    We note that, this is different from what is know in the literature as size-hiding PSI where the goal is the hide the size of input sets. Here, we only intend to hide the size of the intersection from the server who does not have any inputs or outputs.

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Authors and Affiliations

  1. Microsoft Research, Redmond, USA

    Seny Kamara

  2. University of Calgary, Calgary, Canada

    Payman Mohassel & Saeed Sadeghian

  3. SRI, Menlo Park, USA

    Mariana Raykova

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  1. Seny Kamara
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  2. Payman Mohassel
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  3. Mariana Raykova
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  4. Saeed Sadeghian
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Corresponding author

Correspondence to Payman Mohassel .

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Editors and Affiliations

  1. Carnegie Mellon University, Pittsburgh, Pennsylvania, USA

    Nicolas Christin

  2. University of Calgary, Calgary, Alberta, Canada

    Reihaneh Safavi-Naini

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© 2014 International Financial Cryptography Association

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Kamara, S., Mohassel, P., Raykova, M., Sadeghian, S. (2014). Scaling Private Set Intersection to Billion-Element Sets. In: Christin, N., Safavi-Naini, R. (eds) Financial Cryptography and Data Security. FC 2014. Lecture Notes in Computer Science(), vol 8437. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45472-5_13

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  • DOI: https://doi.org/10.1007/978-3-662-45472-5_13

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