Young Researchers in Electrical and Electronic Engineering (EIConRus)
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Cloud data storages are functioning in the presence of the risks of confidentiality, integrity, and availability related with the loss of information, denial of access for a long time, information leakage, conspiracy and technical failures. In this paper, we provide analysis of reliable, scalable, and confidential distributed data storage based on Multilevel Residue Number System (RNS) and Mignotte secret sharing scheme. We use real cloud providers and estimate characteristics such as the data redundancy, speed of data encoding, and decoding to cope with different user preferences. The analysis shows that the proposed storage scheme increases safety and reliability of traditional approaches and reduces data storage overheads by appropriate selection of RNS parameters.
In this paper, we propose an adaptive model of data storage in a heterogeneous distributed cloud environment. Our system utilizes the methods of secret sharing schemes and error correction codes based on Redundant Residue Number System (RRNS). We consider data uploading, storing and downloading. To minimize data access, we use data transfer mechanism between cloud providers. We provide theoretical analysis and experimental evaluation of our scheme with six real data storage providers. We show how dynamic adaptive strategies not only increase security, reliability, and reduction of data redundancy but allow processing encrypted data. We also discuss potentials of this approach, and address methods for mitigating the risks of confidentiality, integrity, and availability associated with the loss of information, denial of access for a long time, and information leakage.