US science foundation to award $23M for ‘privacy-preserving’ tech

The U.S. National Science Foundation (NSF) has begun soliciting proposals from “qualified researchers and multidisciplinary teams” on the practical deployment and scaling of technologies that will allow data sharing in a privacy-preserving manner. NSF said it expects to make 26 awards totaling $23 million.

The awards will be made as a standard or continuing grant under NSF’s Privacy-Preserving Data Sharing in Practice (PDaSP) program, which “seeks to foster innovative use-inspired and translational research to mature and scale existing models, methodologies, or constructs at the intersection of privacy goals and socio-economic or policy challenges.”

Of particular interest to NSF is the innovation and translation of technologies that empowers data subjects, owners/curators, and other stakeholders to control how privacy-sensitive data is shared and used to maximize the utility of data while minimizing potential harms.

“Data plays a central role in our increasingly digital world, where technological innovations allow for the generation, collection, sharing, analysis and seamless flow of large amounts of privacy-sensitive information. These advances, including the explosive growth and rapid adoption of AI, provide unprecedented opportunities to derive value from data to enable better-informed, data-driven decision-making capabilities, accelerate scientific innovation, and enable societal progress,” NSF said.

“These advances, however, also raise significant concerns related to privacy and possible harm to individuals, enterprises, and society at large,” NSF added. “To unleash a future in which the power of data is leveraged for the benefit of all, it is important to develop practical and easily deployable privacy-preserving data sharing and analytics (PPDSA) technologies.”

NSF stressed that technological advances and the proliferation of data protection and privacy laws has added “significant challenges to developing practical technological and socio-technical PPDSA solutions that are easy-to-use and compliant with regulations within the interconnected multi-jurisdictional environments where privacy-sensitive data is shared and used.”

“While there are promising initial real-world deployments of various PPDSA techniques such as differential privacy, secure multi-party computation, and trusted execution environments, to name a few,” NSF explained, “broad adoption of such technologies has been slow due to challenges related to inadequate understanding of privacy risks and harms, limited access to technical expertise, trust and transparency among participants with regard to data collection and use, uncertainty about legal compliance, financial costs, and technical maturity or deployment readiness of solutions.”

The NSF PDaSP program carries out the October 30, 2023 Presidential Executive Order (EO) on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence.

The EO directed 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 tasked 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.”

The PDaSP program also strives to address key recommendations made in the National Strategy to Advance Privacy Preserving Data Sharing and Analytics issued by the White House in March 2023. 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 overarching aim of Biden’s landmark Executive Order is to “ensure that America leads the way in seizing the promise and managing the risks of artificial intelligence (AI).” It also “establishes new standards for AI safety and security, protects Americans’ privacy, advances equity and civil rights, stands up for consumers and workers, promotes innovation and competition, advances American leadership around the world, and more,” according to the Fact Sheet about the EO that the White House issued at the time the EO was announced.

The White House said that “without safeguards, AI can put Americans’ privacy further at risk. AI not only makes it easier to extract, identify, and exploit personal data, but it also heightens incentives to do so because companies use data to train AI systems. To better protect Americans’ privacy, including from the risks posed by AI, the President calls on Congress to pass bipartisan data privacy legislation to protect all Americans, especially kids.”

The EO directed the following actions:

• Protection of Americans’ privacy by prioritizing federal support for accelerating the development and use of privacy-preserving techniques, including ones that use cutting-edge AI and that let AI systems be trained while preserving the privacy of the training data.
• Strengthen privacy-preserving research and technologies, such as cryptographic tools that preserve individuals’ privacy, by funding a Research Coordination Network to advance rapid breakthroughs and development. The National Science Foundation was tasked with working with this network to promote the adoption of leading-edge privacy-preserving technologies by federal agencies.
• Evaluate how agencies collect and use commercially available information -including information they procure from data brokers – and to strengthen privacy guidance for federal agencies to account for AI risks. This work is to focus on commercially available information containing personally identifiable data.
• Develop guidelines for federal agencies to evaluate the effectiveness of privacy-preserving techniques, including those used in AI systems.

NSF said it expects proposers to consider opportunities and gaps that extend across the computing stack, across development and operations, and across the span of modern deployment scenarios including technologies that may be operated by untrusted parties (e.g., private cloud, public cloud, edge computing).

A central element of the solicitation “is to apply, mature, and scale the use of both hardware and software foundations for sharing data while preserving privacy and appropriate use of that data,” NSF said, adding that, “in that spirit,” the solicitation seeks proposals related to maturing PPDSA technologies to increase the utility of data, accompanied by clear plans for relevant demonstration of the viability of the proposed solutions for one or more identified use-cases and/or application contexts.”

Solicitations can be made by academia, non-profit organizations, and businesses that qualify as small businesses. The NSF PDaSP program seeks proposals on the following projects, with the expected funding ranges for each track as shown:

• Track 1 – Advancing key technologies to enable practical PPDSA solutions. Projects are expected to be budgeted in the $500,000 to $1 million range for up to two years;
• Track 2 – Integrated and comprehensive solutions for trustworthy data sharing in application settings. Projects are expected to be budgeted in the $1 million to $1.5 million range for up to three years;
• Track 3 – Usable tools and testbeds for trustworthy sharing of private or otherwise confidential data. These projects are expected to be budgeted in the $500,000 to $1.5million range for up to three years.

NSF said it anticipates making up to 12 Track 1 awards; up to 7 Track 2 awards; and up to 7 Track 3 awards, “depending on the quality of submissions and the availability of funds.” Proposals are due September 27, 2024.

For more information, see NSF’s PDaSP program page.

The PDaSP program represents the collaborative efforts of the NSF Technology, Innovation, and Partnerships and Computer and Information Science and Engineering directorates, as well as the technology companies Intel and VMware, and industry partners U.S. Federal Highway Administration and the National Institute of Standard and Technology.

NSF’s solicitation welcomes new partners from both the public and private sectors. NSF said those submitting proposals “will be given the option of having their proposals considered for new partner co-funding based on matching areas of interest.”

Potential partners from industry and other federal agencies are directed to contact: TIP-PDaSP-Ask@nsf.gov for more details.

Article Topics

biometric data  |  data privacy  |  data protection  |  data sharing  |  national science foundation  |  research and development  |  U.S. Government