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

    Research output: Contribution to journalArticlepeer-review

    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.
    Original languageEnglish
    Pages (from-to)1173-1185
    Number of pages13
    JournalCluster Comput.
    Volume22
    Issue number4
    DOIs
    Publication statusPublished - 2019

    Keywords

    • Reliability
    • Residue number system
    • Storage
    • Data handling
    • Digital storage
    • Energy storage
    • Iterative decoding
    • Numbering systems
    • Different mechanisms
    • Iterative calculation
    • Performance based
    • Performance evaluations
    • Redundant residue number systems
    • Secret sharing schemes
    • Worst case scenario
    • Error detection

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