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Analysis of Privacy-Preserving Edge Computing and Internet of Things Models in Healthcare Domain.

Naif AlmusallamAbdulatif AlabdulatifFawaz Khaled Alarfaj
Published in: Computational and mathematical methods in medicine (2021)
The healthcare sector is rapidly being transformed to one that operates in new computing environments. With researchers increasingly committed to finding and expanding healthcare solutions to include the Internet of Things (IoT) and edge computing, there is a need to monitor more closely than ever the data being collected, shared, processed, and stored. The advent of cloud, IoT, and edge computing paradigms poses huge risks towards the privacy of data, especially, in the healthcare environment. However, there is a lack of comprehensive research focused on seeking efficient and effective solutions that ensure data privacy in the healthcare domain. The data being collected and processed by healthcare applications is sensitive, and its manipulation by malicious actors can have catastrophic repercussions. This paper discusses the current landscape of privacy-preservation solutions in IoT and edge healthcare applications. It describes the common techniques adopted by researchers to integrate privacy in their healthcare solutions. Furthermore, the paper discusses the limitations of these solutions in terms of their technical complexity, effectiveness, and sustainability. The paper closes with a summary and discussion of the challenges of safeguarding privacy in IoT and edge healthcare solutions which need to be resolved for future applications.
Keyphrases
  • healthcare
  • health information
  • big data
  • electronic health record
  • randomized controlled trial
  • machine learning
  • systematic review
  • mental health
  • social media
  • deep learning
  • room temperature