Kotevska, O.
, Johnson, J.
and Kusne, A.
(2022),
Analyzing Data Privacy for Edge Systems, IEEE International Conference on Smart Computing, Espoo, FI, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=934685
(Accessed October 13, 2025)
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Analyzing Data Privacy for Edge Systems
Published
Author(s)
Olivera Kotevska, Jordan Johnson,
Abstract
Internet-of-Things (IoT)-based streaming applications are all around us. Currently, we are transitioning from IoT processing being performed on the cloud to the edge. While moving to the edge provides significant networking efficiency benefits, IoT edge computing creates significant data privacy concerns. We propose a methodology that can successfully privacy protect the continual data streams generated by sensors on the edge device. We implement local differential privacy on streaming data and incorporate Bayesian inference and Gaussian process to evaluate the privacy policy. We demonstrate our methodology on a real-world smart meter testbed and identify the optimal privacy protection settings.Proceedings Title
IEEE International Conference on Smart Computing
Conference Dates
June 20-24, 2022
Conference Location
Espoo, FI
Pub Type
Conferences
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Created July 14, 2022, Updated August 29, 2025