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Big Data and IoT for U-healthcare Security

  • Mechelle Grace Zaragoza
  • Haeng-Kon Kim
  • Roger Y. Lee
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 719)

Abstract

Big Data is a latest topic of interest by many researchers because of its big potential applied in many areas of science and technology. Big Data is by far captivating strong roots in the healthcare ecosystem, but this healthcare data are becoming more complex, which are challenging to solve using common database management tools or simply the traditional data processing application along with the security systems. On the other hand, IoT remainds you to track your health like fitness devices, calorie meters, heart rate monitors, to name a few up to your fridge reminding you that it is basically running out of water.” Big Data and IoT are built on networks and cloud computing of gathering data using sensors but challenges using both especially the security for health care is very vital. IoT and Big Data have the potential to transform the way healthcare providers use sophisticated technologies from their clinical and other data repositories and make informed decisions, but without the right security and encryption solution, Big Data and IoT can mean big problems, especially on healthcare security systems. In this study, we discuss the use and application of IoT and Big Data for u-health care. We have presented this architecture to address the mentioned challenges in this study. Data privacy of patient and user data is a critical requirement. The architecture will access controls to medical device data. The patient should be in control of what is being viewed by whom and will allow him/her to view and set the access control policies, maintaining anonymity and masking of data wherever possible.

Keywords

U-health care IoT Big Data Security systems 

Notes

Acknowledgements

This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the C-ITRC (Convergence Information Technology Research Center) support program (IITP-2016-H8601-15-1007) supervised by the IITP (Institute for Information & Communication Technology Promotion).

This research was supported by the International Research & Development Program of the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT, and Future Planning (Grant Number: K 2014075112).

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Mechelle Grace Zaragoza
    • 1
  • Haeng-Kon Kim
    • 1
  • Roger Y. Lee
    • 2
  1. 1.Catholic University of DaeguGyeongsanSouth Korea
  2. 2.Central Michigan UniversityMount PleasantUSA

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