Project Grant 2453092
- This National Science Foundation (NSF) Project Grant award under the Technology, Innovation, and Partnerships (CFDA 47.084) program provides $1,297,636 to The Trustees of the University of Pennsylvania to develop the Trusted Integration Data Exchange System. This secure platform will enable government agencies, healthcare organizations, and research institutions to perform complex data analysis on jointly held sensitive datasets while maintaining compliance with data sharing policies and...
- This Project Grant award from the National Science Foundation (NSF) under the Technology, Innovation, and Partnerships (TIP) program (CFDA 47.084) supports research to develop novel approaches for enabling participatory privacy protections for AI training data. The $120,511 award to the Fred Hutchinson Cancer Center in Seattle, WA will engage a multi-disciplinary team to conduct ethnographic and computational research. The key objectives are to: (1) identify socio-technical decision points and...
- The National Science Foundation (NSF) awarded a $490,133 Project Grant under the Computer and Information Science and Engineering (CISE) program to the FPF Education and Innovation Foundation. This three-year grant, commencing on July 1, 2024, supports the establishment of a Research Coordination Network (RCN) for Privacy Preserving Data Sharing and Analytics. The RCN is bringing together experts from academia, industry, and government to address challenges in developing, deploying, and...
- This $117,451 federal Project Grant awarded by the National Science Foundation (NSF) under the NSF Technology, Innovation, and Partnerships (TIP) program (CFDA 47.084) supports research to develop novel approaches that can help Public Interest Technology (PIT) organizations deploy data safeguards when building AI systems. The project engages a multi-disciplinary team to conduct ethnographic and computational research on using disclosure limitation techniques, including differential privacy, to...
- This Project Grant award from the National Science Foundation (CFDA 47.084 - NSF Technology, Innovation, and Partnerships) provides $115,643.00 to develop FLTEST, an interdisciplinary testbed to automate privacy and robustness evaluations in federated learning systems. The project aims to address gaps in existing tools by developing automated test orchestration frameworks, implementing privacy attack simulation models, creating configuration vulnerability detection systems, and building...
- This National Science Foundation (NSF) Project Grant award under the Technology, Innovation, and Partnerships (CFDA 47.084) program provides $121,650 to Virginia Polytechnic Institute & State University (Virginia Tech) to develop the FLTEST testbed. The project aims to address challenges in verifying the privacy and robustness of federated learning systems, which enable AI model training across multiple data sources without directly sharing private data. The testbed will automate the...
- The National Science Foundation Division of Computer and Network Systems awarded a $199,076 Project Grant to the FPF Education And Innovation Foundation for collaborative research titled "A Large-Scale, Longitudinal Resource to Advance Technical and Legal Understanding of Textual Privacy Information." The three-year award runs from July 1, 2021 to June 30, 2024 under the Computer and Information Science and Engineering program (CFDA #47.070). The grant will support the development of a...
- This federal Project Grant award from the U.S. Department of Energy (DOE) Office of Science Financial Assistance Program (CFDA 81.049) provides $209,911.79 in funding to the FPF Education And Innovation Foundation. The purpose of this 3-year award, effective July 1, 2024, is to support a Research Coordination Network (RCN) focused on privacy-preserving data sharing and analytics. The foundation, a non-profit organization specializing in privacy research and policy, will leverage this funding...
- 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...
- The National Science Foundation (NSF) awarded a $119,876 Project Grant under the NSF Technology, Innovation, and Partnerships (CFDA 47.084) program to the Regents of the University of Minnesota to design, develop, and sustain FLTEST, an interdisciplinary testbed that automates privacy and robustness evaluations in federated learning systems. This project aims to address challenges in existing privacy-preserving AI systems by developing comprehensive testing tools that can verify the...
PDASP: TRACK 3: TEPPIT: TESTBED FOR PRIVACY-PRESERVING TECHNOLOGIES FOR DATA SHARING AND ANALYSIS -ORGANIZATIONS ACROSS GOVERNMENT, HEALTHCARE, FINANCE, AND RESEARCH NEED TO SHARE AND ANALYZE DATA TO SOLVE IMPORTANT PROBLEMS, BUT CURRENT METHODS FOR PROTECTING PERSONAL PRIVACY WHILE SHARING DATA ARE INADEQUATE AND DIFFICULT TO EVALUATE. RESEARCHERS AND PRACTITIONERS STRUGGLE TO DETERMINE WHICH PRIVACY PROTECTION METHODS WORK BEST FOR DIFFERENT SITUATIONS, HOW MUCH PRIVACY THEY ACTUALLY PROVIDE, AND WHAT TRADE-OFFS EXIST BETWEEN PRIVACY PROTECTION AND DATA USEFULNESS. THIS CREATES BARRIERS TO SAFE DATA SHARING THAT COULD OTHERWISE ENABLE MEDICAL BREAKTHROUGHS, IMPROVE GOVERNMENT SERVICES, AND ADVANCE SCIENTIFIC DISCOVERY. THIS PROJECT ADDRESSES THIS PROBLEM BY BUILDING AND OPERATING A COMPREHENSIVE TESTING FACILITY THAT ALLOWS RESEARCHERS AND PRACTITIONERS TO EVALUATE, COMPARE, AND IMPROVE PRIVACY PROTECTION TECHNOLOGIES FOR DATA SHARING AND ANALYSIS. THIS WORK SERVES THE NATIONAL INTEREST BY STRENGTHENING DATA PRIVACY PROTECTIONS ACROSS CRITICAL SECTORS, ENABLING SECURE COLLABORATION FOR NATIONAL SECURITY AND PUBLIC HEALTH INITIATIVES, SUPPORTING AMERICAN COMPETITIVENESS IN PRIVACY-PRESERVING ARTIFICIAL INTELLIGENCE TECHNOLOGIES, AND ACCELERATING THE DEVELOPMENT OF TRUSTWORTHY DATA SHARING SYSTEMS THAT PROTECT INDIVIDUAL RIGHTS WHILE ADVANCING SCIENTIFIC PROGRESS. THIS PROJECT BUILDS AND OPERATES THE TESTBED FOR PRIVACY-PRESERVING TECHNOLOGIES FOR DATA SHARING AND ANALYSIS, A COMPREHENSIVE EVALUATION INFRASTRUCTURE TO SUPPORT ASSESSMENT, COMPARATIVE ANALYSIS, VULNERABILITY ANALYSIS, PRIVACY RISK ASSESSMENTS, PRIVACY-UTILITY TRADE-OFF ANALYSIS OF PRIVACY-PRESERVING DATA SHARING AND ANALYSIS TECHNOLOGIES AND THEIR APPLICATIONS. THE PROJECT EXTENDS THE EXISTING MID-SCALE RESEARCH INFRASTRUCTURE FOR SECURITY AND PRIVACY RESEARCH WITH DIVERSE EVALUATION SCENARIOS, SPECIALIZED SOFTWARE TOOLS AND USER INTERFACES, AND FOCUSED COMMUNITY BUILDING FOR PRIVACY-PRESERVING DATA ANALYSIS RESEARCH. THE RESEARCH ACTIVITIES INCLUDE DEVELOPING A RICH, MODULAR, EXTENSIBLE AND COMPOSABLE EVALUATION SCENARIO FRAMEWORK WITH SAMPLE TECHNOLOGIES AND APPLICATIONS THAT ALLOW RESEARCHERS TO REUSE, COMBINE, AND EXTEND EVALUATION WORKFLOWS TO EXPLORE SPECIFIC RESEARCH QUESTIONS. THE TESTBED WILL PROVIDE SPECIALIZED HARDWARE SYSTEMS AND SOFTWARE TOOLS, INCLUDING VIRTUAL AND BARE-METAL MACHINES WITH DIFFERENT TRUSTED COMPUTE TECHNOLOGIES, SERVERS WITH GRAPHICS PROCESSING UNITS, AND RESOURCE-CONSTRAINED EMBEDDED PROCESSORS AND INTERNET OF THINGS DEVICES, ALL CONNECTED BY USER-SPECIFIED EMULATED NETWORKS. THE PROJECT WILL GROW THE RESEARCH COMMUNITY THROUGH WORKSHOPS, TUTORIALS, AND MEETINGS AT COMMUNITY EVENTS, AS WELL AS THROUGH SUPPORT FOR RESEARCH ARTIFACT STORAGE AND REUSE TO PROMOTE SHARING, COLLABORATION, AND REPRODUCIBLE RESEARCH. THE TESTBED WILL IMPROVE PRIVACY TECHNOLOGIES AND APPLICATIONS, ACCELERATE RESEARCH MATURATION AND TRANSITION TO PRACTICE, SUPPORT COMMUNITY BUILDING, AND ENHANCE WORKFORCE EDUCATION IN PRIVACY-PRESERVING DATA ANALYSIS METHODS. 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.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $22.5k | 8/28/25 |