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SOCI^+: An Enhanced Toolkit for Secure OutsourcedComputation on Integers

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arxiv 2309.15406 v1 pith:AEQ5LOKX submitted 2023-09-27 cs.CR

classification cs.CR
keywords securesocicomputationintegersprotocolencryptionoutsourcedcommunication
verification ladder T0 review T1 audit T2 compute T3 formal
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Secure outsourced computation is critical for cloud computing to safeguard data confidentiality and ensure data usability. Recently, secure outsourced computation schemes following a twin-server architecture based on partially homomorphic cryptosystems have received increasing attention. The Secure Outsourced Computation on Integers (SOCI) [1] toolkit is the state-of-the-art among these schemes which can perform secure computation on integers without requiring the costly bootstrapping operation as in fully homomorphic encryption; however, SOCI suffers from relatively large computation and communication overhead. In this paper, we propose SOCI+ which significantly improves the performance of SOCI. Specifically, SOCI+ employs a novel (2, 2)-threshold Paillier cryptosystem with fast encryption and decryption as its cryptographic primitive, and supports a suite of efficient secure arithmetic computation on integers protocols, including a secure multiplication protocol (SMUL), a secure comparison protocol (SCMP), a secure sign bit-acquisition protocol (SSBA), and a secure division protocol (SDIV), all based on the (2, 2)-threshold Paillier cryptosystem with fast encryption and decryption. In addition, SOCI+ incorporates an offline and online computation mechanism to further optimize its performance. We perform rigorous theoretical analysis to prove the correctness and security of SOCI+. Compared with SOCI, our experimental evaluation shows that SOCI+ is up to 5.4 times more efficient in computation and 40% less in communication overhead.

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Cited by 1 Pith paper

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  1. Pura: An Efficient Privacy-Preserving Solution for Face Recognition

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    Pura lets twin cloud servers perform face recognition directly on encrypted feature vectors using threshold Paillier encryption, with exact accuracy and up to 16x speedup at database size 1,000.

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