The PIMAWAT Project (Collaborative Research: IMR: MM-1-B: Privacy in Internet Measurements Applied To WAN and Telematics, supported by NSF CISE) will demonstrate new methods to provide data networking datasets that respect end-user privacy, but are still able to support new research in allow network protocols, security, privacy, and machine learning. Our insight is that most data today sent over the wide-area network (WAN) is encrypted, so our 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 focus 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.
The broader impacts of PIMAWAT will be to make it easier for researchers to collect and share network data through new tools and best-practices for privacy-respecting data scrubbing.
PIMAWAT is supported by NSF/CISE as a CISE IMR award CNS-2319409.
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