Abstract
The wide use of wearable devices rises a lot of concerns about the privacy and security of personal data that are collected and stored by such services. This concern is even higher when such data is produced by healthcare monitoring wearable devices and thus the impact of any data leakage is more significant. In this work a classification of the wearable devices used for healthcare monitoring is conducted, and the most prominent relevant privacy and security issues and concerns are presented. Furthermore, a brief review of alternative approaches that can eliminate most of such issues, including federated learning, homomorphic encryption, and tinyML, is presented. The aim of this work is to present the privacy and security concerns in healthcare monitoring wearable devices, as well as some solutions in hot topics about these issues.
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Boumpa, E., Tsoukas, V., Gkogkidis, A., Spathoulas, G., Kakarountas, A. (2022). Security and Privacy Concerns for Healthcare Wearable Devices and Emerging Alternative Approaches. In: Gao, X., Jamalipour, A., Guo, L. (eds) Wireless Mobile Communication and Healthcare. MobiHealth 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 440. Springer, Cham. https://doi.org/10.1007/978-3-031-06368-8_2
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