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An Optimized Integrated Framework of Big Data Analytics Managing Security and Privacy in Healthcare Data

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Abstract

Big data analytics has anonymously changed the overall global scenario to discover knowledge trends for future decision making. In general, potential area of big data application tends to be healthcare, where the global burden is to improve patient diagnostic system and providing patterns to assure the privacy of the end users. However, data constraints exists on real data which needs to be accessed while preserving the security of patients for further diagnostic analysis. This advancement in big data needs to addressed where the patient right needs to maintained while the disclosure of knowledge discovery for future needs are also addressed. To, embark and acknowledge the big data environment its adherently important to determine the cutting-edge research which can benefit end users and healthcare practioners to discover overall prognosis and diagnosis of disease while maintaining the concerns for privacy and security of patient data. In current state of art, we tried to address the big data analytics approach while maintain privacy of healthcare databases for future knowledge discovery. The current objective was to design and develop a novel framework which can integrate the big data with privacy and security concerns and determine knowledgably patterns for future decision making. In the current study we have utilized big data analytical technique for patients suffering from Human Immunodeficiency Virus (HIV) and Tuberculosis (TB) coinfection to develop trends and detect patterns with socio economic factors. Further, a novel framework was implemented using unsupervised learning technique in STATA and MATLAB 7.1 to develop patterns for knowledge discovery process while maintain the privacy and security of data. The study overall can benefit end users to predict future prognosis of disease and combinatorial effects to determining varied policies which can assist patients with needs.

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Acknowledgements

This research work is catalyzed and supported by Indo-Polish joint research grant DST/INT/POL/P-02/2014 and National Council for Science and Technology Communication (NCSTC) research grant 5753/IFD/2015-16 funded by Department of Science and Technology (DST), Ministry of Science and Technology (Govt. of India), New Delhi, India [Grant recipient: Dr. Harleen Kaur].

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Authors and Affiliations

  1. Amity University, Noida, India

    Ritu Chauhan

  2. Department of Computer Science and Engineering, School of Engineering Sciences, and Technology, Jamia Hamdard, New Delhi, India

    Harleen Kaur

  3. School of Computing, Engineering and Digital Technologies, Teesside University, Office P1.07a, Phoenix Building, Stephenson Street, Middlesbrough, TS1 3BA, UK

    Victor Chang

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  1. Ritu Chauhan
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  2. Harleen Kaur
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Correspondence to Harleen Kaur.

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Chauhan, R., Kaur, H. & Chang, V. An Optimized Integrated Framework of Big Data Analytics Managing Security and Privacy in Healthcare Data. Wireless Pers Commun 117, 87–108 (2021). https://doi.org/10.1007/s11277-020-07040-8

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