Skip to main content

A Detailed Survey Study on Various Issues and Techniques for Security and Privacy of Healthcare Records

  • Conference paper
  • First Online:
Intelligent Sustainable Systems

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 213))

Abstract

It is noticed that the exponential data growth in the healthcare domain is manageable by the application of Big Data architecture and techniques. Various Machine Learning (ML) and Big Data techniques are influencing healthcare. It is essential to propose a secure and smart healthcare information system with the latest security mechanism. Similarly, provisions have to be made to secure classified healthcare records in the cloud. Cryptosystems, service-oriented architecture, secure multi-party computation, and secret share schemes are some of the security mechanism methods. Evaluation of a classification model in a cloud computing environment is considered in this paper for privacy preserving. For the success of healthcare organizations, a detailed survey study about privacy and security aspects is also dealt with in this paper. This has resulted in machine learning-based secured data processing of healthcare records in the cloud environment.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 219.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 279.99
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. Abouelmehdi, K., Beni‑Hessane, A., Khaloufi, H.: Big healthcare data: preserving security and privacy. J. Big Data. 5(1) 2018

    Google Scholar 

  2. Barni, M., Failla, P., Lazzeretti, R.: Efficient privacy-preserving classification of ECG signals. In: First IEEE International Workshop on, Information Forensics and Security, et al.: WIFS 2009, IEEE, pp. 91–95 (2009)

    Google Scholar 

  3. Bhadani, A.K., Jothimani, D.: Big data: challenges, opportunities and realities. In: Singh, M.K., Kumar, D.G. (eds.) Effective Big Data Management and Opportunities for Implementation, pp. 1–24 (2016)

    Google Scholar 

  4. Bost, R., Popa, R.A., Tu, S., Goldwasser, S.: Machine learning classification over encrypted data. NDSS (2015)

    Google Scholar 

  5. Gandomi, A., Haider, M.: Beyond the hype: big data concepts, methods, and analytics. Int. J. Inf. Manage. 35(2), 137–144 (2015)

    Article  Google Scholar 

  6. Kaur, P., Sharmab, M., Mittal, M.: Big data and machine learning based secure healthcare framework. In: International Conference on Computational Intelligence and Data Science (ICCIDS 2018), Procedia Comput. Sci. 132, 1049–1059 (2018)

    Google Scholar 

  7. Kruse, C.S., Goswami, R., Raval, Y., Marawi, S.: Challenges and opportunities of big data in healthcare: a systematic review. JMIR Med Inf. 4(4) (2016)

    Google Scholar 

  8. Lee, I.: Big data: dimensions, evolution, impact, and challenges. Bus. Horiz. 60(3), 293–303 (2017)

    Article  Google Scholar 

  9. Li, P., Li, J., Huang, Z., Gao, C.-Z., Chen, W.-B., Chen, K.: Privacy-preserving outsourced classification in cloud computing. Cluster Comput. 21, 277–286 (2018)

    Google Scholar 

  10. Liu, X., Lu, R., Ma, J., et al.: Privacy-preserving patient-centric clinical decision support system on naive Bayesian classification. IEEE J. Biomed. Health Inf. 20(2), 655–668 (2016)

    Article  Google Scholar 

  11. Marwan, M., Kartit, A., Ouahmane, H.: Security enhancement in healthcare cloud using machine learning. In: The First International Conference On Intelligent Computing in Data Sciences. Procedia Comput. Sci. 127, 388–397 (2018)

    Article  Google Scholar 

  12. Ozgur, C., Kleckner, M., Li, Y: Selection of statistical software for solving big data problems: a guide for businesses, students, and universities. Sage Open. 1–12 (2015)

    Google Scholar 

  13. Raj, J.S.: A novel information processing in IoT based real time health care monitoring system. J. Electron. 2(03), 188–196 (2020)

    Google Scholar 

  14. Wang, H.: IoT based clinical sensor data management and transfer using blockchain technology. J. ISMAC 2(03), 154–159 (2020)

    Article  Google Scholar 

  15. Zhang, T., Zhu, Q.: Dynamic differential privacy for ADMMbased distributed classification learning. IEEE Trans. Inf. Forensics Secur. 12(1), 172–187 (2017)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Chaithra, M.H., Vagdevi, S. (2022). A Detailed Survey Study on Various Issues and Techniques for Security and Privacy of Healthcare Records. In: Raj, J.S., Palanisamy, R., Perikos, I., Shi, Y. (eds) Intelligent Sustainable Systems. Lecture Notes in Networks and Systems, vol 213. Springer, Singapore. https://doi.org/10.1007/978-981-16-2422-3_15

Download citation

Publish with us

Policies and ethics