Big Data for Healthcare

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  • 7/25/2019 Big Data for Healthcare

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    Big Data for Healthcare

    Abstract

    Big data techniques are spreading also in medical research. By these techniques is possible

    extract information from complex heterogeneous sources, realizing longitudinal studies focused to

    correlate the patient status with biometric parameters. The rise of big data, however, also raises

    challenges in terms of privacy, security, data ownership, data stewardship, and governance. In this

    paper, we propose a secure and private data management framework that addresses both the security

    and privacy issues in the management of medical data in outsourced databases. The proposed

    framework ensures the security of data by using semantically secure encryption schemes to keep

    data encrypted in outsourced databases.

    There has been a tremendous growth in health data collection since the development of

    !lectronic "edical #ecord $!"#% systems. &uch collected data is further shared and analysed for

    diverse purposes. 'espite many benefits, data collection and sharing have become a big concern as

    it threatens individual privacy. The framework also provides a differentially private query interface

    that can support a number of &() queries and complex data mining tasks. *e experimentally

    evaluate the performance of the proposed framework, and the results show that the proposed

    framework is practical and has low overhead.