@inproceedings{d44a97fe509842bd96a60085ec64c988,
title = "Analyzing Data Privacy for Edge Systems",
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.",
keywords = "Bayesian, Gaussian process, IoT, algorithms, edge, privacy, streaming data",
author = "Olivera Kotevska and Jordan Johnson and {Gilad Kusne}, A.",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 8th IEEE International Conference on Smart Computing, SMARTCOMP 2022 ; Conference date: 20-06-2022 Through 24-06-2022",
year = "2022",
doi = "10.1109/SMARTCOMP55677.2022.00058",
language = "English",
series = "Proceedings - 2022 IEEE International Conference on Smart Computing, SMARTCOMP 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "223--228",
booktitle = "Proceedings - 2022 IEEE International Conference on Smart Computing, SMARTCOMP 2022",
}