SaTC: TTP: Small: Experimental Platform for Rapid Prototyping and Deployment of Secure Multi-Party Protocols

SaTC：TTP：小型：安全多方协议快速原型设计和部署的实验平台

• 批准号: 2213057
• 负责人: Marina Blanton
• 金额: $ 60万
• 依托单位: SUNY at Buffalo
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-15 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2213057&HistoricalAwards=false
• 关键词: SaTC; TTP; Small; Experimental; Platform

The goal of this transition-to-practice project is to build an experimental platform for prototyping and deployment of secure multi-party computation applications. Secure multi-party computation is a concept that permits computing on private data distributed across different data sources by protecting the data via cryptographic means throughout the computation and thus conducting the computational task without learning the data. A variety of different techniques and tools have been developed in the past for secure computation with private data, but their deployment remains slow due to complexity of the techniques, a lack of sufficient expertise in organizations, and poor usability of the available tools. This project facilitates easier development and deployment of secure multi-party computation applications developed by application designers. This goal is accomplished by improving and extending a general-purpose secure multi-party computation compiler called PICCO. The resulting platform can be used by both researchers and programmers who are not domain experts.One of the primary features of the developed platform is the generality of the computation it supports. Namely, a program written in a variant of a conventional programming language is transformed into an implementation of the corresponding secure multi-party computation protocol and additional supporting programs. The platform is extensible and configurable to the needs of specific applications and their computational setup. A novel component includes a convenient web-based user interface for private data entry and output recovery generated at the time of program compilation. A part of the effort also consists of developing educational materials for facilitating the use of secure computation in courses and educational programs and helping local non-profit organizations set up and run privacy-preserving data analysis.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这个过渡到实践的项目的目标是建立一个实验平台的原型和安全的多方计算应用程序的部署。安全多方计算是一种概念，其允许通过在整个计算过程中经由密码手段保护数据来对分布在不同数据源上的私有数据进行计算，从而在不学习数据的情况下进行计算任务。过去已经开发了各种不同的技术和工具用于私有数据的安全计算，但是由于技术的复杂性、组织中缺乏足够的专业知识以及可用工具的可用性差，它们的部署仍然缓慢。该项目有助于更轻松地开发和部署由应用程序设计人员开发的安全多方计算应用程序。这一目标是通过改进和扩展一个通用的安全多方计算编译器PICCO来实现的。该平台的主要特点之一是它所支持的计算的通用性。也就是说，以常规编程语言的变体编写的程序被转换成对应的安全多方计算协议和附加支持程序的实现。该平台是可扩展的和可配置的，以满足特定应用程序及其计算设置的需求。一个新颖的组件包括一个方便的基于Web的用户界面，用于在程序编译时生成的私有数据输入和输出恢复。该奖项的一部分还包括开发教育材料，以促进在课程和教育计划中使用安全计算，并帮助当地非营利组织建立和运行隐私保护数据分析。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Secure and Accurate Summation of Many Floating-Point Numbers

许多浮点数的安全且准确的求和

• DOI: 10.56553/popets-2023-0090
• 发表时间: 2023
• 期刊: Proceedings on Privacy Enhancing Technologies
• 作者: Blanton, Marina;Goodrich, Michael T.;Yuan, Chen
• 通讯作者: Yuan, Chen

Multi-Party Replicated Secret Sharing over a Ring with Applications to Privacy-Preserving Machine Learning

• DOI: 10.56553/popets-2023-0035
• 发表时间: 2023-01
• 期刊: Proc. Priv. Enhancing Technol.
• 作者: Alessandro N. Baccarini;Marina Blanton;Chen Yuan