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A Survey of Big Data Security Solutions in Healthcare

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Abstract

Today data is a strategic asset and organizational goal is to maximize the value of their information. The concept of big data is now treated from different points of view covering its implications in many fields remarkably including Healthcare. Healthcare data is progressively being digitized and the Healthcare era is expansively using new machineries. Thus the medical data is increasing day by day has reached a momentous size all over the world. Although this data is being addressed as the basic to offer treasured insights and sinking cost, the security and privacy issues are so irresistible that medical industry is not capable to take full benefit of it. Privacy of Healthcare is a significant feature overseen by medical acts thus, the data must be secured from dwindling into the wrong hands or from being hacked. Due to the growing threats of loss and outflows from personal data and augmented acceptance of cloud technologies it is important to secure current Healthcare big data domain. This paper aims to present the state-of-the-art security and privacy issues in big data as pragmatic to Healthcare industry and discuss some available data privacy, data security, users’ access control mechanisms and approaches.

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References

  1. Martınez Sesmero, J.M.: Big data application and utility for the healthcare system. FarmHosp 39(2), 69–70 (2015)

    Google Scholar 

  2. Shin, D., Sahama, T., Gajanayake, R.: Secured e-health data retrieval in DaaS and big data. In: Proceedings of the 2013 IEEE 15th International Conference on e-Health Networking, Applications and Services, (Healthcom 2013), pp. 255–259. IEEE, Lisbon, Portugal, October 2013

    Google Scholar 

  3. Chang, V.A.: Amodel to compare cloud and non-cloud storage of big data. Future Gener. Comput. Syst. 57, 56–76 (2016)

    Article  Google Scholar 

  4. Huang, T., Lan, L., Fang, X., An, P., Min, J., Wang, F.: Promises and challenges of big data computing in health sciences. Big Data Res. 2(1), 2–11 (2015)

    Article  Google Scholar 

  5. Firican, G.:The 10 Vs of Big Data, TDWI, 8 February 2017. https://tdwi.org/articles/2017/02/08/10-vs-of-big-data.aspx. Accessed 23 Apr 2018

  6. Chen, C.L.P., Zhang, C.Y.: Data-intensive applications, challenges, techniques and technologies: a survey on big data. Inf. Sci. 275, 314–347 (2014)

    Article  Google Scholar 

  7. Logica, B., Magdalena, R.: Using big data in the academic environment. Procedia Econ. Financ. 33, 277–286 (2015)

    Article  Google Scholar 

  8. Agrawal, D., El Abbadi, A., Arora, V.,et al.: Mind your Ps and Vs: a perspective on the challenges of big data management 6 wireless communications and mobile computing and privacy concerns. In: Proceedings of the 2015 International Conference on Big Data and Smart Computing, (BIGCOMP 2015), pp. 1–6, Republic of Korea, February 2015

    Google Scholar 

  9. Sabar, N.R., Abawajy, J., Yearwood, J.: Heterogeneous cooperative co-evolution memetic differential evolution algorithm for big data optimization problems. IEEE Trans. Evol. Comput. 21(2), 315–327

    Article  Google Scholar 

  10. Jina, X., Waha, B., Chenga, X., Wanga, Y.: Significance and challenges of big data research. Big Data Res. 2, 59–64 (2015)

    Article  Google Scholar 

  11. Mirza, M.A., Habib, M.A.: Optimized energy ingestion in IoT enabled sensor nodes: a survey. J. Softw. Eng. Intell. Syst. 2(3), 3 (2017). E-ISSN: 2518–8739

    Google Scholar 

  12. Big data in HealthCare. https://www.google.com/imgres?imgurl=http

  13. Widmer, A., Schaer, R., Markonis, D., Müller, H.: Gesture interaction for content-based medical image retrieval. In: Proceedings of the 4th ACM International Conference on Multimedia Retrieval, pp. 503–506. ACM, New York (2014)

    Google Scholar 

  14. Jina, X., Waha, B., Chenga, X., Wanga, Y.: E-health for security and privacy in health caresystem using hadoop map reduce. Big Data Res. 2, 59–64 (2015)

    Article  Google Scholar 

  15. Youssef, A.E.: A framework for secure healthcare systems based on big data analytics in mobile cloud computing environments. Int. J. Ambient Syst. Appl. (IJASA) 2(2) (2014)

    Google Scholar 

  16. Gunamalai, C., Sivasubramanian, S.: Novel method of security and privacy for personal medical record and DICOM images in cloud computing. ARPN J. Eng. Appl. Sci. 2, 59–64 (2015)

    Google Scholar 

  17. Masud, M., Hossain, M.S.: Secure data-exchange protocol in a cloud-based collaborative health care environment. Big Data Res. 2, 59–64 (2017)

    Google Scholar 

  18. Subhasri, P., Padmapriya, A.: Authentication based access control mechanism for ensuring privacy of DICOM contents in public cloud. Aust. J. Basic Appl. Sci. 11(10), 128–136 (2017)

    Google Scholar 

  19. Al Hamid, H.A., Mizanur, Sk. Md.: A security model for preserving the privacy of medical big data in a healthcare cloud using a fog computing facility with pairing-based cryptography. IEEE Access 2, 59-64 (2016)

    Google Scholar 

  20. Sathya, S., Sethukarasi, T.: Efficient privacy preservation technique for healthcare records using big data. In: International Conference On Information Communication And Embedded System (ICICES 2016) (2016)

    Google Scholar 

  21. Victor, N., Lopez, D., Abawajy, J.H.: Privacy models for big data: a survey. Int. J. Big Data Intell. 3(1), 61–75

    Article  Google Scholar 

  22. Sarkar, B.K.: Big data for secure healthcare system: a conceptual design. Big Data Croos Mark 2, 59–64 (2017)

    Google Scholar 

  23. Ondiege, B., Clarke, M., Mapp, G.: Exploring a new security framework for remote patient monitoring devices. Big Data Res. 2, 59–64 (2017)

    Google Scholar 

  24. Yang, C., Lin, W., Liu, M.: A novel triple encryption scheme for hadoop-based cloud data security. In: 2014 Fourth International Conference on Emerging Intelligent Data and Web Technologies (2014)

    Google Scholar 

  25. Zhang, R., Liu, L.: Security models and requirements for healthcare application clouds. In: 2017 Fourth International Conference on Emerging Intelligent Data and Web Technologies (2017)

    Google Scholar 

  26. Gholami, A., Laure, E.: Security and privacy of sensitive data in cloud computing: a survey of recent developments, vol. 2. Springer (2016)

    Google Scholar 

  27. Vinoth Kumar, B., Ramaswami, M., Swathika, P.: Data security on patient monitoring for future healthcare application. Int. J. Comput. Appl. 163(6), 0975–8887 (2017)

    Google Scholar 

  28. Khan, F.A., Alia, A., et al.: A cloud-based healthcare framework for security and patients’ data privacy using wireless body area networks. In: The 2nd International Workshop on Communications and Sensor Networks (ComSense-2014) (2014)

    Article  Google Scholar 

  29. Chaudhry, J.A., Tariq, U., Amin, M.A., Rittenhouse, R.G.: Sinkhole vulnerabilities in wireless sensor networks. Int. J. Secur. Appl. 8(1), 401–410 (2014)

    Google Scholar 

  30. Rittenhouse, R.G., Chaudry, J.A., Lee, M.: Security in graphical authentication. Int. J. Secur. Appl. 7(3), 347–356 (2013)

    Google Scholar 

  31. Jabbar, S., Ahmad, M., Malik, K.R., Khalid, S., Chaudhry, J., Aldabbas, O.: Designing an energy-aware mechanism for lifetime improvement of wireless sensor networks: a comprehensive study. Mobile Netw. Appl. 23, 1–14 (2018)

    Article  Google Scholar 

  32. Malik, K.R., Farhan, M., Habib, M.A., Khalid, S., Ahmad, M., Ghafir, I.: Remote access capability embedded in linked data using bi-directional transformation: issues and simulation. Sustain. Cities Soc. 38, 662–674 (2018)

    Article  Google Scholar 

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Correspondence to Mudassar Ahmad .

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

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Siddique, M., Mirza, M.A., Ahmad, M., Chaudhry, J., Islam, R. (2018). A Survey of Big Data Security Solutions in Healthcare. In: Beyah, R., Chang, B., Li, Y., Zhu, S. (eds) Security and Privacy in Communication Networks. SecureComm 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 255. Springer, Cham. https://doi.org/10.1007/978-3-030-01704-0_21

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  • DOI: https://doi.org/10.1007/978-3-030-01704-0_21

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-030-01704-0

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