4.7 Article

SOCI: A Toolkit for Secure Outsourced Computation on Integers

Journal

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIFS.2022.3211707

Keywords

Servers; Protocols; Security; Computational efficiency; Homomorphic encryption; Costs; Computer architecture; Secure computation; secure outsourced computation; homomorphic encryption; data security and privacy

Funding

  1. Singapore National Research Foundation NCR Award [NRF2018NCR-NSOE004-0001]
  2. AXA Research Fund
  3. Lee Kong Chian Professorship
  4. National Natural Science Foundation of China [62072109, U1804263, 62132013, 61702105, 61932011]
  5. Key Research and Development Programs of Shaanxi [2021ZDLGY06-03]
  6. Guangdong Basic and Applied Basic Research Foundation [2019B1515120010]
  7. Guangdong Key Research and Development Plan 2020 [2020B0101090002]
  8. National Key Research and Development Plan 2020 [2020YFB1005600]

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This paper proposes a secure outsourced computation method, called SOCI, based on partially homomorphic encryption and a twin-server architecture, which enables efficient computation on encrypted integers and improves the security and correctness of the computations.
Secure outsourced computation is a key technique for protecting data security and privacy in the cloud. Although fully homomorphic encryption (FHE) enables computations over encrypted data, it suffers from high computation costs in order to support an unlimited number of arithmetic operations. Recently, secure computations based on interactions of multiple computation servers and partially homomorphic encryption (PHE) were proposed in the literature, which enable an unbound number of addition and multiplication operations on encrypted data more efficiently than FHE and do not add any noise to encrypted data; however, these existing solutions are either limited in functionalities (e.g., computation on natural numbers only) or leak information of the underlying data. To tackle these shortcomings, this paper proposes Secure Outsourced Computation on Integers (SOCI) based on PHE and a twin-server architecture. Compared with the existing solutions, SOCI supports computations on encrypted integers (vs. natural numbers) and greatly improves the security and correctness of the computations. Results of theoretical analysis and experimental evaluation show that SOCI outperforms existing solutions in computation and communication efficiencies.

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