Project Grant 2439941

Award Date 5/1/25
Completion Date 4/30/30
Dollars Obligated $377K
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Cambridge, MA 02139, USA
Similar Awards
The Massachusetts Institute of Technology (MIT) was awarded a $500,000 Project Grant from the National Science Foundation (NSF) Division of Computer and Network Systems. The award is part of the NSF's Computer and Information Science and Engineering program (CFDA 47.070) and will support research into practical private information retrieval from October 1, 2021 to September 30, 2024. Specifically, MIT researchers will develop techniques to advance the security and privacy of data access...
The National Science Foundation (NSF) awarded a $387,044 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to Arizona State University to improve the fundamental limits of privacy-enhancing technologies (PETs). The research aims to develop new PET methods that optimize the balance between preserving individual privacy and enabling comprehensive data analysis for societal benefit in domains such as healthcare, education, and resource allocation. Key...
The National Science Foundation (NSF) awarded a $400,000 Project Grant under the Computer and Information Science and Engineering (CFDA #47.070) program to the University of Illinois for a 4-year collaborative research project on privacy-preserving machine learning on graph-structured data. The project aims to develop innovative, efficient algorithms for training and updating large-scale graph neural network models while preserving the privacy of sensitive graph data across applications in areas...
The National Science Foundation (NSF) awarded a $300,000 EAGER grant to the Massachusetts Institute of Technology (MIT) under the NSF Technology, Innovation, and Partnerships program (CFDA 47.084). The project aims to preserve privacy in the use of digital currencies, particularly central bank digital currencies (CBDCs), by developing cryptographic approaches such as pseudonymization, zero-knowledge proofs, and private information retrieval. The research will evaluate design choices for...
The National Science Foundation awarded a $174,855 Project Grant to Michigan Technological University under the Computer and Information Science and Engineering program (CFDA 47.070). The grant supports development of techniques to enable secure machine learning queries over encrypted databases in cloud computing. Specifically, the university will develop an index-aided approach employing encryption of individual data items and generation of secure index items to simultaneously achieve strong...
This Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering program (CFDA 47.070) is focused on accelerating privacy-preserving machine learning as a service. The key objectives are to: (1) orchestrate information representation and model sparsity in the encryption domain to reduce memory and computation footprint; (2) overcome high overhead associated with multi-party computation (MPC)-based solutions through techniques like...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program Project Grant award in the amount of $137,541 provides funding to Tufts University for research to develop algorithms and solutions to guarantee anonymity in network communications. The award addresses the fundamental challenge of obscuring meta-information about who is communicating with whom, when, and for how long, while mitigating increased communication and network congestion issues. The...
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...
The National Science Foundation (NSF) awarded a $179,055 Project Grant to the University of Virginia under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant supports collaborative research to develop privacy-preserving algorithms for fundamental problems in graph mining and network science. The project aims to create scalable, accurate graph differential privacy algorithms for applications like healthcare, social networks, finance, and computational...
The National Science Foundation awarded a $600,000 Project Grant to the Trustees of Boston University under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The three-year award will support research into developing new differentially private stochastic optimization algorithms for training neural networks while preserving individual privacy. Specifically, the grantee will investigate fundamental tradeoffs between privacy and performance in modern...

This National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) project grant award to the Massachusetts Institute of Technology (MIT) will develop a suite of new privacy-preserving web services. The $377,003 grant, awarded on May 1, 2025, will fund the creation of three private web services: private machine-learning inference, private search, and private web browsing. The project aims to enable internet users to enjoy web services without revealing their sensitive personal data to providers. This will require developing new cryptographic primitives, including protocols for private matrix multiplication, private nearest-neighbor search, and distributional private information retrieval. The educational aspects will focus on developing undergraduate content and an open-source textbook on security and systems. The award reflects NSF's mission to advance scientific knowledge and technological innovation in computing and information science.

Generated 6/17/25, 3:42 AM