Toward Practical Privacy-Preserving Analytics for IoT and Cloud-Based Healthcare Systems

Modern healthcare systems now rely on advanced computing methods and technologies, such as Internet of Things (IoT) devices and clouds, to collect and analyze personal health data at an unprecedented scale and depth. Patients, doctors, healthcare providers, and researchers depend on analytical model...

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Vydáno v:IEEE internet computing Ročník 22; číslo 2; s. 42 - 51
Hlavní autoři: Sharma, Sagar, Chen, Keke, Sheth, Amit
Médium: Journal Article
Jazyk:angličtina
Vydáno: IEEE 01.03.2018
Témata:
Analytical models
application of privacy preserving protocols
Cloud computing
Computational modeling
Data models
Data privacy
Internet
IoT healthcare and privacy concerns
Medical services
pervasive healthcare services
precision healthcare
Privacy
privacy preserving outsourced computation
privacy risks in modern healthcare
ISSN:1089-7801, 1941-0131
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Shrnutí:Modern healthcare systems now rely on advanced computing methods and technologies, such as Internet of Things (IoT) devices and clouds, to collect and analyze personal health data at an unprecedented scale and depth. Patients, doctors, healthcare providers, and researchers depend on analytical models derived from such data sources to remotely monitor patients, early-diagnose diseases, and find personalized treatments and medications. However, without appropriate privacy protection, conducting data analytics becomes a source of a privacy nightmare. In this article, we present the research challenges in developing practical privacy-preserving analytics in healthcare information systems. The study is based on kHealth-a personalized digital healthcare information system that is being developed and tested for disease monitoring. We analyze the data and analytic requirements for the involved parties, identify the privacy assets, analyze existing privacy substrates, and discuss the potential tradeoff among privacy, efficiency, and model quality.
ISSN:1089-7801
1941-0131
DOI:10.1109/MIC.2018.112102519