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CAREER: Distributed Differential Privacy via Secure Multiparty Computation

CAREER: Distributed Differential Privacy via Secure Multiparty Computation
职业:通过安全多方计算实现分布式差分隐私
批准号:
2238442
负责人:
Joseph Near
金额:
$54.89万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-04-15 至 2028-03-31

项目摘要

项目成果

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中文摘要
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英文摘要
The increasing rate of collection and analysis of personal data has led to new privacy and security concerns. Differential privacy is a promising framework for protecting individual privacy, but deploying it in practice remains a challenge. Bugs in differential privacy systems are difficult to find, and can result in unexpected privacy failures. In addition, such systems often require collecting sensitive data on central servers; a compromise of these servers could result in a catastrophic loss of privacy. This project aims to develop tools for addressing both challenges. The project's novelties are: (a) new techniques for verifying that programs correctly implement differential privacy, and (b) new applications of cryptography to protect the security of data during processing. The project's broader significance and importance lies in its potential to enable the broader deployment of correct, secure implementations of formal privacy guarantees for individuals in data processing systems.The central goal of this project is to enable the construction of correct, scalable systems that satisfy differential privacy without the need for a trusted data curator. To this end, the project aims to design both new secure protocols and new techniques for ensuring the correctness of systems built with those protocols. Specific research goals of the project include (1) the design of new secure protocols that leverage properties of differential privacy to increase performance and scale to millions of participants; (2) new tools for evaluating these protocols at scale; (3) new automated program analyses for verifying the correctness of secure protocols; and (4) new program analyses and automated testing approaches for checking the correctness of differentially private systems built on secure protocols. This project includes the development of educational materials, including a programming-oriented textbook suitable for an undergraduate course on secure computation.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.
期刊论文(1)
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科研奖励(0)
会议论文
OLYMPIA: A Simulation Framework for Evaluating the Concrete Scalability of Secure Aggregation Protocols
OLYMPIA:用于评估安全聚合协议的具体可扩展性的模拟框架
DOI: --
发表时间: 2024
期刊: IEEE Conference on Secure and Trustworthy Machine Learning
影响因子: --
作者: [Ngong, Ivoline C., Gibson, Nicholas, Near, Joseph P.]
通讯作者: Near, Joseph P.
国内基金
海外基金
Graphon mean field games with partial observation and application to failure detection in distributed systems
  • 批准号:
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2025
  • 负责人:
    MATHIEULOUROCHLAURIERE
  • 依托单位: