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Complete Data Deletion Based on Hadoop Distributed File System

Published: 22 October 2019 Publication History

Abstract

There is a disk residual problem for the deletion mechanism of the Hadoop file storage system. This paper proposes a "plug and play" deletion method to achieve the purpose of completely deleting data. After simulation and recovery experiments, this method can effectively destroy the original data. At the same time, this method can be applied to some Big data clusters which are based on Hadoop. It does not need to redeploy the cluster and can be directly deployed in the already running big data cluster.

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Cited By

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  • (2021)Towards Understanding the Challenges of Data Remanence in Cloud Computing: A ReviewAdvances in Cyber Security10.1007/978-981-33-6835-4_33(495-507)Online publication date: 5-Feb-2021

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    cover image ACM Other conferences
    CSAE '19: Proceedings of the 3rd International Conference on Computer Science and Application Engineering
    October 2019
    942 pages
    ISBN:9781450362948
    DOI:10.1145/3331453
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 22 October 2019

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    Author Tags

    1. Data residual
    2. Delete data completely
    3. Hadoop

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    CSAE 2019

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    Overall Acceptance Rate 368 of 770 submissions, 48%

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    Cited By

    View all
    • (2021)Towards Understanding the Challenges of Data Remanence in Cloud Computing: A ReviewAdvances in Cyber Security10.1007/978-981-33-6835-4_33(495-507)Online publication date: 5-Feb-2021

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