Skip to main content
SpringerLink
Log in

A Survey on Privacy Preserving Approaches on Health Care Big Data in Cloud

  • Conference paper
  • First Online:
Proceeding of the International Conference on Computer Networks, Big Data and IoT (ICCBI - 2019) (ICCBI 2019)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 49))

Included in the following conference series:

Abstract

To reform and enhance healthcare services, the use of information technology is increasing in an unprecedented manner. This technological advancement results in generating substantial medical data from various Healthcare related things. This Medical Big data has a maximum prospective to upgrade patients’ treatment and follow up. We anticipate to flare-up some preventable infections, and we can significantly reduce the Healthcare delivery cost, by using the Medical Big data. One specific pattern observed in the medical services industry is serial shifting data to the cloud. By shifting data to the cloud, the accessibility of the patient’s medical history in real-time is possible and it can reduce costs. Though we enjoy multiple advantages of cloud computing for Medical Big data, we face specific security issues of our data stored in the cloud. In this paper, a brief analysis on various approaches used to protect the healthcare related information stored in the cloud and further they are secured using cryptographic techniques.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
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

Institutional subscriptions

References

  1. Li, Z.-R., et al.: A secure electronic medical record sharing mechanism in the cloud computing platform. In: 2011 IEEE 15th International Symposium on Consumer Electronics (2011)

    Google Scholar 

  2. Liu, W., Liu, X., Liu, J., Wu, Q., Zhang, J., Li, Y.: Auditing and revocation enabled role-based access control over outsourced private EHRs. In: 2015 IEEE 17th International Conference on High-Performance Computing and Communications (HPCC), New York, NY, USA, pp. 336–341 (2015)

    Google Scholar 

  3. Bhateja, R., et al.: Enhanced timing enabled proxy re-encryption model for e-health data in the public cloud. In: 2017 IEEE International Conference on Advances in Computing, Communications, and Informatics (ICACCI) (2017)

    Google Scholar 

  4. Attrapadung, N., Furukawa, J., Imai, H.: Forward-secure and searchable broadcast encryption with short ciphertexts and private keys. ASIACRYPT 2006, LNCS 4284, pp. 161–177. Springer, Heidelberg (2006)

    Google Scholar 

  5. Gowda, B.K., Sumathi, R.: Hierarchy attribute-based encryption with timing enabled privacy preserving keyword search mechanism for e-health clouds. In: 2017 2nd IEEE International Conference on Recent Trends in Electronics Information & Communication Technology (RTEICT), India, 19–20 May 2017 (2017)

    Google Scholar 

  6. Jayalakshmi, V., Nayak, L.: Protecting medical big data in a healthcare cloud using elliptic curve cryptography. J. Adv. Res. Dyn. Control Syst. 10(11-Special Issue), 1054–1059 (2018)

    Google Scholar 

  7. Liu, X., Deng, R.H., Choo, K.R., Yang, Y.: Privacy-preserving outsourced clinical decision support system in the cloud. IEEE Trans. Serv. Comput. (2017). https://doi.org/10.1109/tsc.2017.2773604

  8. Li, P., Guo, S., Miyazaki, T., Xie, M., Hu, J., Zhuang, W.: Privacy-preserving access to big data in the cloud. IEEE Cloud Comput. 3(5), 34–42 (2016)

    Article  Google Scholar 

  9. Al Hamid, H.A., et al.: A security model for preserving the privacy of medical big data in a healthcare cloud using a fog computing facility with pairing-based cryptography, pp. 2169–3536. IEEE (2017)

    Google Scholar 

  10. Karthiban, M.K., Raj, J.S.: Bıg data analytics for developing secure internet of everything. J. ISMAC 1(02), 129–136 (2019)

    Google Scholar 

  11. Rabieh, K., Akkaya, K., Karabiyik, U., Qamruddin, J.: A secure and cloud-based medical records access scheme for on-road emergencies. In: 2018 15th IEEE Annual Consumer Communications & Networking Conference (CCNC) (2018)

    Google Scholar 

  12. Yang, Y.: Attribute-based data retrieval with semantic keyword search for e-health cloud. J. Cloud Comput. 4(1), 10 (2015)

    Article  Google Scholar 

  13. Chen, Y.Y., Lu, J.C., Jan, J.K.: A secure EHR system based on hybrid clouds. J. Med. Syst. 36(5), 3375–3384 (2012). https://doi.org/10.1007/s10916-012-9830-6

    Article  Google Scholar 

  14. Valanarasu, M.R.: Smart and secure Iot and AI integration framework for hospital environment. J. ISMAC 1(03), 172–179 (2019)

    Article  Google Scholar 

  15. Abbas, A., Khan, S.U.: A review on the state-of-the-art privacy-preserving approaches in the e-health clouds. IEEE J. Biomed. Heal. Inf. 18(4), 1431–1441 (2014)

    Article  Google Scholar 

  16. Yang, Y., Ma, M.: Conjunctive keyword search with designated tester and timing enabled proxy re-encryption function for e-health clouds. IEEE Trans. Inf. Forensics Secur. 11(4), 746–759 (2016)

    Google Scholar 

  17. Kuo, M.H.: Opportunities and challenges of cloud computing to improve health care services. J Med Internet Research 13(3), e67 (2011)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Computing Sciences, Vels Institute of Science, Technology and Advanced Studies (VISTAS), Chennai, India

    Lipsa Nayak & V. Jayalakshmi

Authors
  1. Lipsa Nayak
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. V. Jayalakshmi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to V. Jayalakshmi .

Editor information

Editors and Affiliations

  1. Department of CSE, Vaigai College of Engineering, Melur, Tamil Nadu, India

    A. Pasumpon Pandian

  2. Department of Business Administration, The Gerald Schwartz School of Business, StFX University, Antigonish, NS, Canada

    Ram Palanisamy

  3. Electrical and Computer Engineering, University of Applied Sciences, Egaleo, Attiki, Greece

    Klimis Ntalianis

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Nayak, L., Jayalakshmi, V. (2020). A Survey on Privacy Preserving Approaches on Health Care Big Data in Cloud. In: Pandian, A., Palanisamy, R., Ntalianis, K. (eds) Proceeding of the International Conference on Computer Networks, Big Data and IoT (ICCBI - 2019). ICCBI 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 49. Springer, Cham. https://doi.org/10.1007/978-3-030-43192-1_4

Download citation

Publish with us

Policies and ethics

Search

Navigation