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Home > Archive>Volume 34, Issue 11, 2023 >5408-5423. DOI:10.13328/j.cnki.jos.006737
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Secure Computation of Range and Sum of Extremums on Distributed Datasets
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TP309

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    Abstract:

    Due to the continuous breakthrough and development of information and communication technologies, information access has become convenient on the one hand. On the other hand, private information is now easier to leak than before. The combination of the intelligent field and secure multiparty computation (SMC) technology is expected to solve privacy protection problems. Although SMC has solved many different privacy protection problems so far, problems that remain to be settled are numerous. Research results about the SMC of range and the sum of extremums are currently seldom reported. As a common statistical tool, range and sum of extremums have been widely used in practice. Therefore, the secure computation of range and the sum of extremes are of great research significance. This study proposes a new encoding method and solves two types of SMC problems by the method: One is the secure computation of range, and the other is that of the sum of extremums. The new encoding method is combined with the Lifted ElGamal threshold cryptosystem to design a secure range computation protocol for distributed private datasets in the scenario in which multiple parties participate and each party has one data. Then, the new encoding method is slightly modified for the secure computation of the sum of extremums in the same scenario. On this basis, the study further modifies the new encoding method and combines it with the Paillier cryptosystem to design a protocol for the secure computation of range and the sum of extremums on distributed private datasets in the scenario in which two parties participate and each party has more than one data. Furthermore, this study proves that the proposed protocols are secure in the semi-honest model with the simulation paradigm. Finally, the complexities of these protocols are tested by simulation experiments. The results of the efficiency analysis and experiments show that the simple and efficient proposed protocols can be widely used in practical applications and are important tools for solving many other SMC problems.

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李顺东,家珠亮,赵雪玲.分布式数据集极差与极值和的保密计算.软件学报,2023,34(11):5408-5423

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History
  • Received:November 29,2021
  • Revised:February 21,2022
  • Online: May 18,2023
  • Published: November 06,2023
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