Performance evaluation of secret sharing schemes with data recovery in secured and reliable heterogeneous multi-cloud storage

A. Tchernykh, V. Miranda-López, M. Babenko, F. Armenta-Cano, G. Radchenko, A.Y. Drozdov, A. Avetisyan

    Publikation: Beitrag in FachzeitschriftArtikelBegutachtung

    Abstract

    Properties of redundant residue number system (RRNS) are used for detecting and correcting errors during the data storing, processing and transmission. However, detection and correction of a single error require significant decoding time due to the iterative calculations needed to locate the error. In this paper, we provide a performance evaluation of Asmuth-Bloom and Mignotte secret sharing schemes with three different mechanisms for error detecting and correcting: Projection, Syndrome, and AR-RRNS. We consider the best scenario when no error occurs and worst-case scenario, when error detection needs the longest time. When examining the overall coding/decoding performance based on real data, we show that AR-RRNS method outperforms Projection and Syndrome by 68% and 52% in the worst-case scenario. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.
    OriginalspracheEnglisch
    Seiten (von - bis)1173-1185
    Seitenumfang13
    FachzeitschriftCluster Comput.
    Jahrgang22
    Ausgabenummer4
    DOIs
    PublikationsstatusVeröffentlicht - 2019

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