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MESSB–LWE: multi-extractable somewhere statistically binding and learning with error-based integrity and authentication for cloud storage

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Abstract

The concept of cloud envisioned cyber-physical systems is a practical technology that allows users to interact with each other while transferring data in the cloud. In cyber-physical systems, cloud storage utilizes data deduplication techniques to improve the performance of its applications. However, this method exposes sensitive data and causes security risks. Various research related to cloud storage has been conducted. Despite the advantages of this technology, it lacks the necessary security features and high performance. In the proposed method, a victim's virtual computer is moved to the cloud without interfering with the other processes running on the network. It protects against the attacks caused by encrypting the data with a cryptographically binding hash. Post-Quantum Cryptographic techniques, such as lightweight Multi-Extractable Somewhere Statistically Binding and Learning With Error authenticate data sharing protocols (MESSB–LWE), have been used. These allow for safe data sharing across geographically scattered physical devices and clients with lightweight concepts. The numerical analysis of MESSB–LWE is carried out in different stages, and the results show that it has incredible performance and practicality when compared to the literature. Finally, the authors have explored a couple of factors that should be considered for future research work in authentication for securing remote systems in the cloud environment.

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Correspondence to Dilli Babu Salvakkam.

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Salvakkam, D.B., Pamula, R. MESSB–LWE: multi-extractable somewhere statistically binding and learning with error-based integrity and authentication for cloud storage. J Supercomput 78, 16364–16393 (2022). https://doi.org/10.1007/s11227-022-04497-1

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  • DOI: https://doi.org/10.1007/s11227-022-04497-1

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