A secure framework for mHealth data analytics with visualization

Denise Ferebee, Vivek Shandilya, Chase Wu, Janet Ricks, David Agular, Karyn Cole, Byron Ray, Aukii Franklin, Candice Titon, Zongmin Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Mobile technology is changing the data collection and analytics in traditional healthcare practice. The distributed and real time nature of the operation brings security challenges in the gathering, processing, and analysis of personal biometrics data gathered by various wearable health monitoring devices. We present a security framework which identifies the anomalies not only based on the range of bio-metric parameters but also the history and the context. The values of the bio-metric parameters are used to construct the matrices to define the events. The matrices are de-noised using Random Matrix Theory. The correlation between different parameters is captured by the Pearson correlation. A canonical database, populated over time, of the vital signs of the patient and the values of the related bio-metric parameters through correlation network provide the history and context to detect anomalies. The security of the data collected in real time is very critical in establishing if an event is an anomaly. Our security framework ensures user authentication, confidentiality using encryption, confirms source device identity and packet level data validation. We provide a fully functional centralized visualization system to keep track of both patient and the doctors involved during any event of interest/ concern.

Original languageEnglish (US)
Title of host publication2016 IEEE 35th International Performance Computing and Communications Conference, IPCCC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509052523
DOIs
StatePublished - Jan 17 2017
Event35th IEEE International Performance Computing and Communications Conference, IPCCC 2016 - Las Vegas, United States
Duration: Dec 9 2016Dec 11 2016

Publication series

Name2016 IEEE 35th International Performance Computing and Communications Conference, IPCCC 2016

Other

Other35th IEEE International Performance Computing and Communications Conference, IPCCC 2016
CountryUnited States
CityLas Vegas
Period12/9/1612/11/16

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture

Keywords

  • Arduino
  • biometrics
  • correlation
  • cyber security
  • heart rhythm

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