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

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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.

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Acknowledgments

The work is partially supported by Russian Federation President Grant SP-1215.2016, and Russian Foundation for Basic Research (RFBR) 18-07-01224.

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Authors and Affiliations

  1. CICESE Research Center, Ensenada, BC, Mexico

    Andrei Tchernykh, Vanessa Miranda-López & Fermin Armenta-Cano

  2. North-Caucasus Federal University, Stavropol, Russia

    Mikhail Babenko

  3. South Ural State University, Chelyabinsk, Russia

    Andrei Tchernykh & Gleb Radchenko

  4. Moscow Institute of Physics and Technology, Moscow, Russia

    Alexander Yu. Drozdov

  5. Institute for System Programming, Moscow, Russia

    Andrei Tchernykh & Arutyun Avetisyan

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  1. Andrei Tchernykh
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Correspondence to Andrei Tchernykh.

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Tchernykh, A., Miranda-López, V., Babenko, M. et al. Performance evaluation of secret sharing schemes with data recovery in secured and reliable heterogeneous multi-cloud storage. Cluster Comput 22, 1173–1185 (2019). https://doi.org/10.1007/s10586-018-02896-9

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