CRII: SaTC: Efficient Secure Multiparty Computation of Large-Scale, Complex Protocols

CRII：SaTC：大规模、复杂协议的高效安全多方计算

• 批准号: 1464113
• 负责人: Yan Huang
• 金额: $ 17.5万
• 依托单位: Indiana University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-05-01 至 2019-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1464113&HistoricalAwards=false
• 关键词: CRII; SaTC; Efficient; Secure; Multiparty

Many challenging real world problems, e.g., voting and blind auction, require computation over sensitive data supplied by multiple mutually-distrustful entities. Elegant cryptographic theories have been developed to solve these problems without relying on a mutually-trusted third party. Practitioners also built prototypes capable of securely computing set intersection, AES encryption, Hamming distance, etc. However, many other applications, such as data mining and running universal machines, are far more complex than what can be supported by the state-of-the-art techniques. This work studies new methods and platforms to enable large-scale, complex cryptographic protocols in more efficient ways. Software produced will be released as open-source projects to benefit future research in related areas. One part of this project explores new extensible approaches to accommodate multiple Secure Multiparty Computation (SMC) protocols and enable studying interesting combinations of them, including a new compiler to provide a higher-level abstraction for generating SMC protocols. The other part involves research into several new optimizations to improve the performance and scalability of SMC, through reuse of validated components to amortize validation costs. The educational activities of this project include mentoring both undergraduate and graduate students in applied cryptography research and developing a graduate course in applied cryptography.For further information see the project web site at: http://smc-in-action.soic.indiana.edu

许多具有挑战性的真实的世界问题，例如，投票和盲拍卖需要对多个相互不信任的实体提供的敏感数据进行计算。优雅的密码理论已经被开发出来，以解决这些问题，而不依赖于相互信任的第三方。从业者还建立了能够安全计算集合交集，AES加密，汉明距离等的原型，然而，许多其他应用程序，如数据挖掘和运行通用机器，远比最先进的技术所能支持的复杂得多。这项工作研究了新的方法和平台，以更有效的方式实现大规模，复杂的加密协议。所制作的软件将作为开源项目发布，以利于相关领域的未来研究。该项目的一部分探索了新的可扩展方法，以适应多个安全多方计算（SMC）协议，并使研究它们的有趣组合，包括一个新的编译器，以提供一个更高层次的抽象生成SMC协议。另一部分涉及研究几个新的优化，以提高SMC的性能和可扩展性，通过重用验证的组件，摊销验证成本。该项目的教育活动包括指导本科生和研究生进行应用密码学研究，并开发应用密码学的研究生课程。http://smc-in-action.soic.indiana.edu