Project Grant 2327981
- This Project Grant award from the National Science Foundation's Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $374,291 to Brown University to develop novel tools and techniques for secure multi-party computation (MPC), with a focus on expanding the use cases of private set intersection (PSI). The project aims to bridge the gap between standard PSI and more enriched PSI functionalities, enabling large-scale, privacy-preserving data analytics across...
- This $599,059 National Science Foundation project grant supports the development of secure multi-party computation programming technology at Rensselaer Polytechnic Institute. The goal is to advance compiler frameworks and optimization techniques that allow non-cryptography experts to write efficient privacy-preserving algorithms for applications like machine learning and data analytics. Key deliverables include an intermediate representation for secure computation and novel intra- and...
- This Project Grant from the National Science Foundation Division of Computing and Communication Foundations, under the Computer and Information Science and Engineering federal grant program (CFDA 47.070), provides $400,000 to support research activities focused on improving the efficiency of secure multi-party computation (MPC) techniques. Specifically, the award funds a research collaboration led by Georgia Tech Research Corporation from April 2023 to March 2027 to explore and implement novel...
- This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program provides $600,000 to develop a hybrid solution that integrates the strengths of multi-party computing (MPC) and trusted hardware to enable secure and efficient AI offloading. The project, titled "SHF: SMALL: Practical Privacy-Preserving AI Offloading with Hybridizing Multi-Party Computing and Strongly-Secure Hardware," aims to address the significant...
- This Project Grant award of $164,999 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program is for a project titled "CRII: SATC: TOWARDS COST-EFFICIENT PRIVATE COMPUTATION FOR CLOUD DATA SCIENCE". The objective is to develop techniques that reduce the cost of practical Secure Multiparty Computation (MPC) for data science in the cloud. This will enable more cost-effective collaborative data science on private datasets, leading to...
- This four-year, $400,000 Project Grant from the National Science Foundation's Division of Computing and Communication Foundations, under the Computer and Information Science and Engineering program (CFDA #47.070), will fund research at the University of Illinois to develop new techniques for secure multi-party computation using garbled RAM. Secure multi-party computation allows mutually untrusting parties to jointly evaluate functions on private data, and garbled RAM is a technique to remove...
- This SBIR Phase I Project Grant, awarded by the National Science Foundation (NSF) under the Technology, Innovation, and Partnerships (CFDA 47.084) program, aims to develop a novel data security technology that enables organizations to collaboratively analyze encrypted data. The proposed solution combines fully homomorphic encryption and secure multi-party computation to create an efficient protocol that balances computational efficiency with strong privacy guarantees. This $303,174 award to...
- This $13,843 federal Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program will fund research to develop new computer systems that allow organizations to gain insights from large datasets while keeping individual information completely private. The key research objectives are to: 1) develop new protocols for privacy-preserving data collection that enable servers to compute aggregate statistics over client data without...
- This $600,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research at Northeastern University focused on developing doubly efficient Private Information Retrieval (DEPIR) and fully homomorphic encryption for random-access machines. The key goals of the project are to: 1) achieve practical efficiency for DEPIR and fully homomorphic encryption techniques, 2) explore alternative cryptographic...
- This three-year $599,999 Project Grant from the National Science Foundation's Division of Computing and Communication Foundations, under the Computer and Information Science and Engineering program (CFDA 47.070), will support research into novel methods for computing aggregate statistics on streaming data in a privacy-preserving manner. Specifically, the University of California, Los Angeles will explore efficient algorithms to privately compute telemetry data from user devices sending...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Program project grant, awarded to Purdue University for $600,000 on December 1, 2023, aims to improve the security and efficiency of secure multi-party computation (MPC) technology. MPC enables computations on private data without revealing non-essential information, facilitating collaboration in social, scientific, commercial, and security domains while maintaining privacy. The project will build a mathematical framework to characterize MPC protocols' efficiency and robustness against side-channel attacks, with the goal of guiding secure protocol design and automating threat assessment. The research outcomes are expected to have significant real-world impact by advancing the adoption of this privacy-enhancing technology.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $600.0k | 11/28/23 |