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Cloud-HPA: hierarchical privacy perseverance anatomy for data storage in cloud environment

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Abstract

Sharing the data in the cloud environment may generate some loopholes and backdoor entries for intruders. In concern to the attributes of storage records, generally vertical and horizontal partitioning is used that can acquire resilient privacy strength. The paper portrays privacy perseverance hierarchy-oriented collaborative architecture to store data over the cloud. To improve privacy and not let attackers break through, an algorithm has been designed, which keeps the sensitive and non-sensitive records isolated by applying different properties such as cryptography & Anonymization series. It includes generalization, l-diversity & t-closeness methods. An archetype model in the cloud environment has been implemented for identifying the validity of the proposed algorithm and optimization of architecture. For the evaluation, the unification level has been incorporated into the progressive algorithm that reduces the time and increases speed for the data restructuring which is used in privacy perseverance architecture. Further, the findings incorporate generalized statistical study to identify the behavior of the properties used and the complexity analysis of the work has been presented.

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Data Availability

The datasets generated during and/or analysed during the current study are available in the Electronic Health Record (EHR) Data repository, https://datarade.ai/data-categories/electronic-health-record-ehr-data

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Acknowledgements

This work was supported in part by the Science and Engineering Research Board (SERB) under the Department of Science and Technology (DST), Government of India, and in part by the National Institute of Technology, Kurukshetra, India.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Information Technology, Bhopal, India

    Ashutosh Kumar Singh

  2. Department of Computer Applications, National Institute of Technology, Kurukshetra, India

    Ashutosh Kumar Singh

  3. Department of Computer Science, University of Helsinki, Helsinki, Finland

    Niharika Singh

  4. Department of Computer Science, International Institute of Information Technology, Bangalore, Karnataka, India

    Ishu Gupta

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  1. Ashutosh Kumar Singh
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Correspondence to Ishu Gupta.

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Singh, A.K., Singh, N. & Gupta, I. Cloud-HPA: hierarchical privacy perseverance anatomy for data storage in cloud environment. Multimed Tools Appl 83, 37431–37451 (2024). https://doi.org/10.1007/s11042-023-16674-2

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