This Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program provides $191,421 to the University of California, San Diego (UCSD) to advance research and education in differential privacy. The project aims to develop new algorithms and analytical tools that enable more precise privacy accounting and higher utility in differential privacy. Key research components include: unifying recent breakthroughs in...
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 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 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 $167,158 Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports the development of a customizable, privacy-preserving database analytics system compatible with existing SQL databases. The key products to be delivered under this 4-year award include: Automated tools for analyzing a database schema and interactively developing a flexible privacy model to determine which data elements require differential...
This $209,988 Project Grant award from the National Science Foundation (NSF) Integrative Activities (CFDA 47.083) program supports research at Clemson University to establish theoretical and algorithmic foundations for ensuring differential privacy in decentralized optimization algorithms without losing provable optimality. The key research thrusts include: Investigating the tradeoff between convergence speed and differential privacy in decentralized optimization, Exploring differential...
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...
This National Science Foundation Project Grant of $450,000 will develop simulation-based statistical tools to improve analysis of differentially private data through July 2025. Funded by the Social, Behavioral, and Economic Sciences program (CFDA 47.075), the award supports research to deliver more accurate statistical estimation and inference for data subject to privacy constraints. The grantee, Purdue University, will use computer simulation techniques to address a wide range of statistical...
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...
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...