Privacy-Preserving Data Sharing in Practice

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In today’shyperconnected and device-rich world, increasing computational power and the explosive growth of data present us with tremendous opportunities to enable data-driven, evidence-based decision-making capabilities to accelerate scientific discovery and innovation. However, to be able to responsibly leverage the insights from and power of data, such as for training powerful artificial intelligence (AI) models, it is important to have practically deployable and scalable technologies that allow data sharing in a privacy-preserving manner. While there has been significant research progress in privacy-related areas, privacy-preserving data sharing technologies remain at various levels of maturity in terms of practical deployment. The goals of the PDaSP program are aligned with the Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence (AI EO), which emphasizes the role for privacy-enhancing technologies (PETs) in a responsible and safe AI future. The EO directs NSF to, “where feasible and appropriate, prioritize research — including efforts to translate research discoveries into practical applications — that encourage the adoption of leading-edge PETs solutions for agencies’ use.” It also tasks NSF with “developing and helping to ensure the availability of testing environments, such as testbeds, to support the development of safe, secure, and trustworthy AI technologies, as well as to support the design, development, and deployment of associated PETs.” In addition to meeting these directives in the AI EO, the PDaSP program strives to address key recommendations made in the National Strategy to Advance Privacy Preserving Data Sharing and Analytics (PPDSA). In particular, the program strives to advance the strategy’s priority to “Accelerate Transition to Practice,” which includes efforts to “promote applied and translational research and systems development,” develop “tool repositories, measurement methods, benchmarking, and testbeds,” and “improve usability and inclusiveness of PPDSA solutions.” The PDaSP program welcomes proposals from qualified researchers and multidisciplinary teams in the following tracks with expected funding ranges for proposals as shown below. Track 1: Advancing key technologies to enablepractical PPDSA solutions: Track 1 projects are expected to be budgeted in the $500K - $1M rangefor up to 2 years Track 2: Integratedand comprehensive solutions for trustworthy data sharing in application settings: Track 2 projects are expected to be budgeted in the $1M - $1.5M range for up to 3 years Track 3: Usabletools, and testbeds for trustworthy sharing of private or otherwise confidential data. Track 3 projects are expected to be budgeted in the $500K - $1.5M range for up to 3 years The PDaSP program represents the collaborative efforts of the NSF Technology, Innovation and Partnerships (TIP) and Computer and Information Science and Engineering (CISE) directorates, Intel Corporation and VMware LLC as industry partners, and the U.S. Department of Transportation Federal Highway Administration (FHWA) and the U.S. Department of Commerce National Institute of Standards and Technology (NIST) as federal agency partners. Thissolicitation includes partners from both industry and the federal government, and welcomes new partners from both public and private sectors ahead of the proposal submission deadline.PIs will be given the option of having their proposals considered for new partner co-funding based on matching areas of interest.