Blockchain based Quantum Resistant Signature Algorithm for Data Integrity Verification in Cloud and Internet of Everything

Pranav Shrivastava; Bashir Alam; Mansaf Alam

doi:10.4108/eetsis.5488

Authors

Pranav Shrivastava Jamia Millia Islamia
Bashir Alam Jamia Millia Islamia
Mansaf Alam Jamia Millia Islamia

DOI:

https://doi.org/10.4108/eetsis.5488

Keywords:

Data integrity verification, blind signature algorithm, lattice cryptography, puzzle optimization algorithm, blockchain, upgraded Merkle tree, vacuum filter, quantum resistant

Abstract

INTRODUCTION: The processing and storage capacities of the Internet of Everything (IoE) platform are restricted, but the cloud can readily provide efficient computing resources and scalable storage. The Internet of Everything (IoE) has expanded its capabilities recently by employing cloud resources in multiple ways. Cloud service providers (CSP) offer storage resources where extra data can be stored. These methods can be used to store user data over the CSP while maintaining data integrity and security. The secure storage of data is jeopardized by concerns like malicious system damage, even though the CSP's storage devices are highly centralized. Substantial security advancements have been made recently as a result of using blockchain technology to protect data transported to networks. In addition, the system's inclusive efficacy is enhanced, which lowers costs in comparison to earlier systems.

OBJECTIVES: The main objective of the study is to a blockchain-based data integrity verification scheme is presented to provide greater scalability and utilization of cloud resources while preventing data from entering the cloud from being corrupted.

METHODS: In this paper, we propose a novel method of implementing blockchain in order to enhance the security of data stores in cloud.

RESULTS: The simulations indicate that the proposed approach is more effective in terms of data security and data integrity. Furthermore, the comparative investigation demonstrated that the purported methodology is far more effective and competent than prevailing methodologies.

CONCLUSIONS: The model evaluations demonstrated that the proposed approach is quite effective in data security.

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