Abstract
Storage-as-a-service offers cost savings, convenience, mobility, scalability, redundant locations with a backup solution, on-demand with just-in-time capacity, syncing and updating, etc. While this type of cloud service has opened many opportunities, there are important considerations. When one uses a cloud provider, their data are no longer on their controllable local storage. Thus, there are the risks of compromised confidentiality and integrity, lack of availability, and technical failures that are difficult to predict in advance. The contribution of this paper can be summarized as follows: (1) We propose a novel mechanism, En-AR-PRNS, for improving reliability in the configurable, scalable, reliable, and secure distribution of data storage that can be incorporated along with storage-as-a-service applications. (2) We introduce a new error correction method based on the entropy (En) paradigm to correct hardware and software malfunctions, integrity violation, malicious intrusions, unexpected and unauthorized data modifications, etc., applying a polynomial residue number system (PRNS). (3) We use the concept of an approximation of the rank (AR) of a polynomial to reduce the computational complexity of the decoding. En-AR-PRNS combines a secret sharing scheme and error correction codes with an improved multiple failure detection/recovery mechanism. (4) We provide a theoretical analysis supporting the dynamic storage configuration to deal with varied user preferences and storage properties to ensure high-quality solutions in a non-stationary environment. (5) We discuss approaches to efficiently exploit parallel processing for security and reliability optimization. (6) We demonstrate that the reliability of En-AR-PRNS is up to 6.2 times higher than that of the classic PRNS.
Highlights
We studied data reliability based on a polynomial residual number system and proposed a configurable, reliable, and secure distributed storage scheme, named
We provided a theoretical analysis of the dynamic storage configurations
We proposed a novel decoding technique based on entropy to increase reliability
Summary
Chervyakov et al (2019) [14] presented cloud storage based on the redundant residual number system (RRNS) It overcomes several issues of the above approach; SSS based on RRNS has a low data coding and decoding speed (Tchernykh et al, 2019 [12]). We propose a novel entropy-based mechanism for improving the reliability of distributed data storage; An En-AR-PRNS scheme is proposed that combines the SSS and error correction codes with multiple failure detection/recovery mechanisms. It can detect and correct more errors than the state-of-the-art threshold-based PRNS;.
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