| NSF Org: |
CNS Division Of Computer and Network Systems |
| Recipient: |
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| Initial Amendment Date: | July 28, 2023 |
| Latest Amendment Date: | September 9, 2024 |
| Award Number: | 2319410 |
| Award Instrument: | Continuing Grant |
| Program Manager: |
Deepankar Medhi
dmedhi@nsf.gov (703)292-2935 CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | October 1, 2023 |
| End Date: | March 31, 2026 (Estimated) |
| Total Intended Award Amount: | $220,133.00 |
| Total Awarded Amount to Date: | $220,133.00 |
| Funds Obligated to Date: |
FY 2024 = $128,925.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
115 JOHN WILDER TOWER MEMPHIS TN US 38152-0001 (901)678-3251 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
101 WILDER TOWER MEMPHIS TN US 38152-3520 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): |
Information Technology Researc, Networking Technology and Syst |
| Primary Program Source: |
01002324DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
The PIMAWAT (Privacy in Internet Measurements Applied to WAN And Telematics) project will demonstrate new methods to provide data networking datasets that respect end-user privacy, while still being able to support new research in network protocols, security, privacy, and machine learning. The main insight is that *most data today sent over the wide-area network (WAN) is encrypted*; thus, the challenge is to demonstrate what data is encrypted, detect and scrub any remaining leaks, and finally anonymize the metadata (who talks to whom) before sharing data.
The intellectual merit of PIMAWAT will be to develop new methods to anonymize network traffic at scale, then use those new algorithms to evaluate potential data leakage, and demonstrate that real-world data sources can be scrubbed for sharing while respecting privacy. PIMAWAT plans to focus the investigator?s prior work on wide-area network data traffic. As possible, it will also explore vehicle telematics as a recently developing dataset that poses unique privacy opportunities and challenges, with a device (not person) focus, yet with geolocation and application details.
The broader impacts of PIMAWAT will be to democratize the potential to collect and share network data through new tools and best-practices for privacy-respecting data scrubbing. Data from this project will enable new approaches in computer science for protocol design and cyber-security, applying AI and machine learning, and will provide early results in the rapidly evolving field of vehicle telematics. PIMAWAT will provide new tools, data, and practices, and encourage use of these methods by other researchers, in classrooms, and by industry.
The PIMAWAT project website will be https://ant.isi.edu/pimawat and its tools and datasets will be provided through https://ant.isi.edu/datasets/ as they are developed during project and after it completes.
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.
Please report errors in award information by writing to: awardsearch@nsf.gov.
