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ISSN 1004-9037
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Edited by: Editorial Board of Journal of Data Acquisition and Processing
P.O. Box 2704, Beijing 100190, P.R. China
Sponsored by: Institute of Computing Technology, CAS & China Computer Federation
Undertaken by: Institute of Computing Technology, CAS
Published by: SCIENCE PRESS, BEIJING, CHINA
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      09 May 2023, Volume 38 Issue 3
    Article

    PRIVACY PRESERVING AND SECURING SENSITIVE DATA (PPSSD) IN CLOUD CONTAINERS USING LSTM AND ECC ALGORITHMS
    Muthakshi S1*, Mahesh K2
    Journal of Data Acquisition and Processing, 2023, 38 (3): 538-547 . 

    Abstract

    Cloud containers on servers can securely and efficiently process data according to the needs of users. Depending upon the cloud service providers policy, preserving privacy of data and preserving sensitive data are carried out using an extra efficient robust techniques. As usage of such server containers increased the allocation of container space to specific users is sorted out with the usage of Long Short-Term Memory (LSTM) algorithm and allocation will be done accordingly. Containers will be classified under cloud servers by generating id to each and they will be further classified as sensitive and non-sensitive data in containers. Non-sensitive data will be preserved in public containers. Sensitive data will be further categorized into user driven sensitive data using rotation forest algorithm and predicting sensitive data aided from training data. Those indicated sensitive data will be secured in privacy preserving containers using ECC encryption. Sensitive id will be generated for each segment of sensitive data and that will be authorized during id matching and merging while retrieving data from containers.

    Keyword

    Cloud Container, Privacy Preserving, Sensitive Data, Non-Sensitive Data, Rotation Forest Algorithm, Elliptic-Curve Cryptography, Sensitive ID generator.


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ISSN 1004-9037

         

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