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arXiv · 2101.02556

Spatial K-anonymity: A Privacy-preserving Method for COVID-19 Related Geospatial Technologies

Rohan Iyer·Regina Rex·Kevin P. McPherson·Darshan Gandhi·Aryan Mahindra·Abhishek Singh·Ramesh Raskar
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Abstract

There is a growing need for spatial privacy considerations in the many geo-spatial technologies that have been created as solutions for COVID-19-related issues. Although effective geo-spatial technologies have already been rolled out, most have significantly sacrificed privacy for utility. In this paper, we explore spatial k-anonymity, a privacy-preserving method that can address this unnecessary tradeoff by providing the best of both privacy and utility. After evaluating its past implications in geo-spatial use cases, we propose applications of spatial k-anonymity in the data sharing and managing of COVID-19 contact tracing technologies as well as heat maps showing a user's travel history. We then justify our propositions by comparing spatial k-anonymity with several other spatial privacy methods, including differential privacy, geo-indistinguishability, and manual consent based redaction. Our hope is to raise awareness of the ever-growing risks associated with spatial privacy and how they can be solved with Spatial K-anonymity.

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Rohan Iyer, Regina Rex, Kevin P. McPherson, Darshan Gandhi, Aryan Mahindra, Abhishek Singh, Ramesh Raskar. 2021-01-04. Spatial K-anonymity: A Privacy-preserving Method for COVID-19 Related Geospatial Technologies. https://arxiv.org/abs/2101.02556

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