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Collaborative Research: Scalable Privacy Verification and Quantification for Multi-Robot Systems
NSF
About This Grant
This project will support research that contributes novel methodologies related to privacy protection of multi-robot systems, promoting the progress of science and advancing national health and prosperity. Due to possible active and passive intruders who may gain access to communication channels and observe the system behaviors, private information can be leaked through robot behaviors. However, existing works on privacy analysis of robot behaviors may not scale when the system dimension increases. This project supports fundamental research that addresses the major challenges in multi-robot systems, privacy analysis, algorithm design, computation, and information theory. The project will contribute to more secure and private robotic systems and increase the usage of robots in various domains to increase efficiency and safety. Existing approaches on privacy analysis of robot behaviors rely on the construction of a deterministic observer, and therefore require an exponential complexity for privacy analysis. To address this, this project will develop a scalable computation framework for analyzing behavior privacy of multi-robot systems, which reduces the computation complexity with quantifiable and acceptable error bounds. Four closely integrated research objectives are planned: (1) Develop a scalable privacy verification framework with only polynomial complexity to verify that there is no privacy leak; (2) Develop a scalable privacy quantification framework to measure the robot’s privacy level subject to noise and uncertainty; (3) Develop an information releasing policy for multi-robot systems to perform collaborative tasks while preserving privacy against compromised robots; and (4) Evaluate and validate the framework on multi-robot patrolling system. Collectively, advances from these research endeavors are expected to make the robotic systems more secure, and will create a new computationally efficient verification mechanism for large multi-agent systems where privacy can be a concern. 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.
Grant Summary
Collaborative Research: Scalable Privacy Verification and Quantification for Multi-Robot Systems is a NSF grant providing up to $334K for university, nonprofit, small business. Applications are due 2028-09-30 (open). Check eligibility and apply with FindGrants.
Focus Areas
Eligibility
How to Apply
Up to $334K
2028-09-30
- 1Confirm your organization is eligible for Collaborative Research: Scalable Privacy Verification and Quantification for Multi-Robot Systems from NSF, checking organization type, location, and any population or project requirements.
- 2Gather the required documents and information, including your organization details, project plan, and budget figures.
- 3Draft your application narrative and budget addressing the funder's priorities and review criteria. FindGrants can draft each section for you to review and edit.
- 4Review every section against the requirements checklist, then export a submission-ready application pack and submit it to NSF before the deadline.
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Collaborative Research: Scalable Privacy Verification and Quantification for Multi-Robot Systems: Frequently Asked Questions
Who is eligible for the Collaborative Research: Scalable Privacy Verification and Quantification for Multi-Robot Systems?
Collaborative Research: Scalable Privacy Verification and Quantification for Multi-Robot Systems is offered by NSF and is generally open to university, nonprofit, small business. It is open to organizations nationwide unless the funder specifies otherwise. Review the specific eligibility terms before applying, since funders set their own requirements around organization type, location, and the population or project being served.
How much funding does the Collaborative Research: Scalable Privacy Verification and Quantification for Multi-Robot Systems provide?
Collaborative Research: Scalable Privacy Verification and Quantification for Multi-Robot Systems provides up to $334K per award from NSF. Actual award sizes depend on the scope of your project, available program funds, and the number of applicants, so build a budget that reflects realistic, allowable costs rather than the maximum figure.
When is the Collaborative Research: Scalable Privacy Verification and Quantification for Multi-Robot Systems deadline?
Applications for Collaborative Research: Scalable Privacy Verification and Quantification for Multi-Robot Systems are due 2028-09-30 (open). Because deadlines can change, verify the date with the funder, NSF, and give yourself enough time to prepare a complete, competitive application before the close date.
How do you apply for the Collaborative Research: Scalable Privacy Verification and Quantification for Multi-Robot Systems?
To apply for Collaborative Research: Scalable Privacy Verification and Quantification for Multi-Robot Systems, confirm your eligibility, gather the required documents, and prepare a narrative and budget that address the funder's priorities. FindGrants guides you step by step and can draft each section, then exports a submission-ready application pack for this grant from NSF.