SaTC: CORE: Medium: Collaborative: New Approaches for Large Scale Secure Computation

SaTC：核心：媒介：协作：大规模安全计算的新方法

• 批准号: 1955620
• 负责人: Arkady Yerukhimovich
• 金额: $ 40.45万
• 依托单位: George Washington University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-15 至 2025-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1955620&HistoricalAwards=false
• 关键词: SaTC; CORE; Medium; Collaborative; New

Secure multi-party computation (MPC) allows multiple distrusting parties to perform joint computations on their data without exposing the data to one another. Due to their promising security guarantees, the cryptographic protocols for MPC have gained unprecedented exposure in the last decade. With the proliferation of large, distributed systems and computations such as Tor and blockchain, there is an urgent need for large-scale MPC to ensure security and privacy for these applications. However, large-scale applications pose some unique challenges for the design of MPC protocols. There are thousands of parties, often with unequal resources, and some number of parties are likely to fail during a protocol execution. This project proposes to design MPC protocols to address these challenges. The project’s novelties are the design of new MPC protocols satisfying the requirements of large-scale distributed applications. Specifically, the investigators put forward a new framework for committee-based MPC for large-scale secure computations. These protocols distribute the computations across thousands of parallel committees to maximize the utilization of available resources for improved throughput. The designed protocols optimally choose committees and committee sub-protocols that optimize resource utilization and security. Additionally, they handle party failure and provide efficient oblivious access and search capabilities over data generated in these computations. The team of researchers combines techniques from prior work on secure computation (MPC) and oblivious data structures to simultaneously achieve all of these goals. The project’s impacts are to enable new classes of privacy-preserving computation, analytics, and applications geared to the needs of real-world distributed systems.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.

安全多方计算（MPC）允许多个不信任方对其数据执行联合计算，而不会将数据暴露给彼此。由于其有前途的安全保证，MPC的加密协议在过去十年中获得了前所未有的曝光。随着Tor和区块链等大型分布式系统和计算的激增，迫切需要大规模MPC来确保这些应用程序的安全性和隐私性。然而，大规模应用对MPC协议的设计提出了一些独特的挑战。有成千上万的参与方，通常具有不平等的资源，并且一些参与方可能在协议执行期间失败。该项目提出设计MPC协议来解决这些挑战。该项目的新颖之处是设计新的MPC协议，满足大规模分布式应用的要求。具体来说，研究人员提出了一个新的框架，用于基于委员会的MPC进行大规模安全计算。这些协议将计算分布在数千个并行委员会中，以最大限度地利用可用资源，提高吞吐量。所设计的协议最佳地选择委员会和委员会子协议，优化资源利用率和安全性。此外，它们还处理参与方失败，并对这些计算中生成的数据提供高效的不经意访问和搜索功能。 研究团队结合了先前在安全计算（MPC）和不经意数据结构方面的工作，同时实现了所有这些目标。该项目的影响是使新类别的隐私保护计算，分析和应用程序，以适应现实世界的分布式系统的需求。该奖项反映了NSF的法定使命，并已被认为是值得通过评估使用基金会的智力价值和更广泛的影响审查标准的支持。

项目成果

Secure Sampling with Sublinear Communication

使用次线性通信进行安全采样

• 发表时间: 2022
• 期刊: Springer
• 作者: Choi, Seung Geol;Dachman-Soled, Dana;Gordon, S. Dov;Liu, Linsheng;Yerukhimovich, Arkady
• 通讯作者: Yerukhimovich, Arkady

The More the Merrier: Reducing the Cost of Large Scale MPC

越多越好：降低大规模 MPC 的成本

• DOI: 10.1007/978-3-030-77886-6_24
• 发表时间: 2021
• 期刊: Annual International Conference on the Theory and Applications of Cryptographic Techniques
• 作者: Gordon, S. Dov;Starin, Daniel;Yerukhimovich, Arkady
• 通讯作者: Yerukhimovich, Arkady

Fighting Fake News in Encrypted Messaging with the Fuzzy Anonymous Complaint Tally System (FACTS)

使用模糊匿名投诉统计系统 (FACTS) 打击加密消息中的假新闻

• DOI: 10.14722/ndss.2022.23109
• 发表时间: 2022
• 期刊: Proceedings 2022 Network and Distributed System Security Symposium
• 作者: Liu, Linsheng;Roche, Daniel S.;Theriault, Austin;Yerukhimovich, Arkady
• 通讯作者: Yerukhimovich, Arkady

When Frodo Flips: End-to-End Key Recovery on FrodoKEM via Rowhammer

• DOI: 10.1145/3548606.3560673
• 发表时间: 2022-11
• 期刊: Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security
• 作者: Michael Fahr;Hunter Kippen;Andrew Kwong;T. Dang;Jacob Lichtinger;Dana Dachman-Soled;Daniel Genkin;Alexander Nelson;Ray A. Perlner;Arkady Yerukhimovich;Daniel Apon

Compressed Oblivious Encoding for Homomorphically Encrypted Search

• DOI: 10.1145/3460120.3484792
• 发表时间: 2021-09
• 期刊: Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security
• 作者: Seung Geol Choi;Dana Dachman-Soled;S. D. Gordon;Linsheng Liu;Arkady Yerukhimovich