Outsourced private set intersection using homomorphic encryption

Authors:
Florian Kerschbaum
Affiliations:
SAP Research, Karlsruhe, Germany
Venue:
Proceedings of the 7th ACM Symposium on Information, Computer and Communications Security
Year:
2012

Citing 8
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CRYPTO'05 Proceedings of the 25th annual international conference on Advances in Cryptology
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FC'10 Proceedings of the 14th international conference on Financial Cryptography and Data Security
Efficient set operations in the presence of malicious adversaries

PKC'10 Proceedings of the 13th international conference on Practice and Theory in Public Key Cryptography

When private set intersection meets big data: an efficient and scalable protocol

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EsPRESSO: Efficient privacy-preserving evaluation of sample set similarity

Journal of Computer Security

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Abstract

Private set intersection enables two parties -- a client and a server -- to compute the intersection of their respective sets without disclosing anything else. It is a fundamental operation -- equivalent to a secure, distributed database join -- and has many applications particularly in privacy-preserving law enforcement. In this paper we present a novel protocol that has linear complexity, is secure in the malicious model without random oracles, is client set size-independent and efficient. Furthermore, the computation of the intersection can be outsourced to an oblivious service provider, as in secure cloud computing. We leverage a completely novel construction for computing the intersection using Bloom filter and homomorphic encryption. For outsourcing we require and introduce a new homomorphic encryption scheme which may be of independent interest.