Project Grant 2220450
- This $500,000 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program will fund research into information-theoretic privacy and security for personalized distributed learning systems at the University of California, Los Angeles from March 2022 through February 2025. The grant aims to design personalized learning models that leverage large-scale collaborative data while maintaining individuals' privacy and requiring trust only in one's own...
- 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...
- The National Science Foundation (NSF) awarded a $538,133 Project Grant under the Computer and Information Science and Engineering (CISE) Federal Grant Program to Rutgers, The State University (Newark Division) to conduct research on privacy-preserving data analysis algorithms for continuously generated online data. The key focus of this 3-year project (August 1, 2025 - July 31, 2028) is to develop novel algorithms that can perform statistical analysis on sensitive user data while guaranteeing...
- 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 awarded a $299,999 Project Grant to the University of California, Los Angeles (UCLA) to assess the relationship between privacy regulations and software development, with the goal of improving rulemaking and compliance. The grant, funded through the NSF's Computer and Information Science and Engineering (CISE) program (CFDA 47.070), will support a multidisciplinary research effort combining legal and engineering expertise. The key products and services to be...
- This $175,000 two-year Project Grant from the National Science Foundation's Division of Computer and Network Systems, under the Computer and Information Science and Engineering program (CFDA 47.070), will support the development of novel local differential privacy techniques to significantly improve the privacy-utility tradeoff in multi-attribute data analysis. The Rochester Institute of Technology will develop techniques exploiting correlation in multi-attribute data and correlated random...
- This National Science Foundation project grant of $300,000 will fund foundational research on differentially private Internet measurement from October 2022 to September 2025. Under the Computer and Information Science and Engineering program, researchers at the University of California Irvine will conduct three thrusts of work to lay the groundwork for deploying differential privacy in processing Internet measurement data. Specifically, Thrust 1 will study existing practices for collecting and...
- This three-year Project Grant from the National Science Foundation's Division of Computer and Network Systems, under the Computer and Information Science and Engineering federal grant program (CFDA 47.070), provides $299,619 to the University of Virginia to lay the foundations for differentially private Internet measurement. Specifically, the award supports three main research thrusts. The first will study existing privacy issues in collecting and sharing Internet measurement data and develop an...
- This Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $279,959 to Carnegie Mellon University to advance the frontiers of differential privacy algorithms for private learning and synthetic data generation. The 5-year research project aims to develop a theoretical framework to better capture practical privacy scenarios, design practical privacy-preserving algorithms, and create auditing...
- This National Science Foundation (NSF) Project Grant award, funded under the Engineering program (CFDA 47.041), supports research to develop a novel framework for privacy-aware and fair data acquisition in multi-agent distributed systems. The $439,961 award to the University of California, Santa Barbara aims to create fair incentives for strategic agents to contribute an appropriate share of private data, enabling efficient and safe operation of critical distributed systems like autonomous...
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 secret-shared data to two non-communicating servers. The goals are to classify functions that can be privately computed over streaming secret-shared data using poly-logarithmic memory, and to advance the state-of-the-art in multi-party computation for internet-scale streaming computations. If successful, the methods developed will enable large-scale and efficient privacy-preserving analysis of streaming data. The award also aims to train graduate and undergraduate students, including those from underrepresented groups, in cryptographic research.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $600.0k | 8/17/22 |