Skip to main content

A Lightweight and Secure Framework for Hybrid Cloud Based EHR Systems

  • Conference paper
  • First Online:

Abstract

Recently Cloud based Electronic Health Records Systems have been developed and are being used in the healthcare industry. Albeit the various benefits of the technology, security, trust and privacy are a major concern. In this paper, we present a secure and affordable framework for EHR storage, leveraging the properties of hybrid cloud in securing data in addition to building low power back-end cluster constructed using low cost single board computers (SBC). We detail requirements for a secure cloud based EHR framework and present the system architecture based on the publisher/subscriber model. The framework is developed and tested on a Hadoop based cloud cluster using SBCs as nodes. Efficiency of the framework is measured in terms of response time for various sizes of Data Blocks containing EHRs.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Yang, J.J., Li, J., Niu, Y.: A hybrid solution for privacy preserving medical data sharing in cloud computing. Future Gener. Comput. Syst. 43(44), 74–86 (2015)

    Article  Google Scholar 

  2. Manoj, R., Alsadoon, A., Prasad, P.W.C., Costadopoulos, N., Ali, S.: Hybrid secure and scalable electronic health record sharing in hybrid cloud. In: 5th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud), pp. 185–190 (2017)

    Google Scholar 

  3. Arora, A., Khanna, A., Rastogi, A., Agarwal, A.: Cloud security ecosystem for data security and privacy. In: 7th International Conference on Cloud Computing, Data Science and Engineering, pp. 288–292 (2017)

    Google Scholar 

  4. Shrestha, M.N., Alsadoon, A., Prasad, C.P., Houran, L.: Enhanced eHealth framework for security and privacy in healthcare. In: 6th International Conference on Digital Information Processing and Communications (ICDIPC), pp. 75–79 (2016)

    Google Scholar 

  5. Suresh, S.: Highly secured cloud based personal health record model. In: International Conference on Green Engineering and Technologies (IC-GET), pp. 1–4 (2015)

    Google Scholar 

  6. Liu, Z., Weng, J., et al.: Cloud-based electronic health record system supporting fuzzy keyword search. Soft Comput. 20(8), 3243–3255 (2016)

    Article  Google Scholar 

  7. US Department of Health and Human Services: Health Insurance Portability and Accountability Act (2017). http://www.hhs.gov/ocr/privacy

  8. Bahga, A., Madisetti, V.K.: Healthcare data integration and informatics in the cloud. Computer 48(2), 50–57 (2015)

    Article  Google Scholar 

  9. Fang, R., et al.: Computational health informatics in the big data age: a survey. ACM Comput. Surv. 49(1), 12 (2016)

    Article  Google Scholar 

  10. Zhou, J., Cao, Z., Dong, X., Lin, X.: PPDM: a privacy-preserving protocol for cloud-assisted e-healthcare systems. IEEE J. Sel. Top. Sig. Process. 9(7), 1332–1344 (2015)

    Article  Google Scholar 

  11. Zhou, J., et al.: PSMPA: patient self-controllable and multi-level privacy-preserving cooperative authentication in distributed m-healthcare cloud computing system. In: IEEE Transactions on Parallel and Distributed Systems, vol. 26, no. 6, pp. 1693–1703, 1 June 2015

    Article  Google Scholar 

  12. Qureshi, B.: Towards a digital ecosystem for predictive healthcare analytics. In: 6th International Conference on Management of Emergent Digital EcoSystems (MEDES 2014), pp. 34–41 (2014)

    Google Scholar 

  13. Page, A., et al.: QT clock to improve detection of QT prolongation in long QT syndrome patients. Heart Rhythm 13(1), 190–198 (2016)

    Article  Google Scholar 

  14. Diffie, W., Hellman, M.: New directions in cryptography. IEEE Trans. Inf. Theor. 22(6), 644–654 (2006)

    Article  MathSciNet  Google Scholar 

  15. Qureshi, B., et al.: Performance of a low cost Hadoop cluster for image analysis in cloud robotics environment. Procedia Comput. Sci. 82, 90–98 (2016)

    Article  Google Scholar 

Download references

Acknowledgements

This work is partially funded by the Robotics and Internet of Things Unit (RIoTU) at Prince Sultan University.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Basit Qureshi .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Qureshi, B., Koubaa, A., Al Mhaini, M. (2018). A Lightweight and Secure Framework for Hybrid Cloud Based EHR Systems. In: Mehmood, R., Bhaduri, B., Katib, I., Chlamtac, I. (eds) Smart Societies, Infrastructure, Technologies and Applications. SCITA 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 224. Springer, Cham. https://doi.org/10.1007/978-3-319-94180-6_20

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-94180-6_20

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-94179-0

  • Online ISBN: 978-3-319-94180-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics