Secure MPC for Analytics as a Web Application
Secure MPC for Analytics as a Web Application
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作为 Web 应用程序进行分析的安全 MPC
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Mayank Varia
中科院分区：
文献类型：
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作者：
A. Lapets;Nikolaj Volgushev;Azer Bestavros;Frederick Jansen;Mayank Varia
公司、政府机构和其他组织一直在分析与其内部运营相关的数据，并取得了巨大的效果，例如在评估绩效或提高效率方面。虽然每个组织自己的数据在内部都很有价值，但来自多个组织的汇总数据可以对组织本身、政策制定者和社会有价值。不幸的是，组织的数据通常是专有和机密的，其发布可能会损害组织的利益。安全多方计算 (MPC) 解决了这种矛盾：可以在计算汇总数据的同时保护每个贡献者的机密性。理论构造已为人所知数十年 [1]-[3]，最近的努力旨在将它们交付给最终用户 [4]-[6]。
Companies, government agencies, and other organizations have been analyzing data pertaining to their internal operations with great effect, such as in evaluating performance or improving efficiency. While each organization’s own data is valuable internally, aggregate data from multiple organizations can have value to the organizations themselves, policymakers, and society. Unfortunately, an organization’s data is often proprietary and confidential, and its release may be potentially deleterious to the organization’s interests. Secure multi-party computation (MPC) resolves this tension: aggregate data may be computed while protecting each contributor’s confidentiality. Theoretical constructs have been known for decades [1]–[3] and recent efforts aim to deliver them to end-users [4]–[6].