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Chowdhury, Tonoy Kanti
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Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Electrical & Electronics Engineering

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Journal : Journal for Technology and Science

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BLOCKCHAIN-INTEGRATED MACHINE LEARNING FOR SECURE DATA MANAGEMENT AND CLOUD COMPUTING Chowdhury, Tonoy Kanti; Mohi uddin, K M
Journal for Technology and Science Vol. 3 No. 1 (2026): Journal for Technology and Science
Publisher : PT ANTIS INTERNATIONAL PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61796/ipteks.v3i1.452

Abstract

Objective : This paper discusses how blockchain and machine learning can work together in improving the security of handling data in cloud computing systems. Method : The framework proposed uses blockchain to provide data integrity and access control and auditability, and machine learning models are used to identify security threats, allocate resources to improve resource use, and enhance performance. Results : It has been shown that machine learning with blockchain will greatly enhance trust, security, and efficiency in the data management of a cloud-based environment. Novelty : The solution to the critical challenges of data security, privacy, integrity, and trust in multi-tenant and decentralized cloud settings is addressed by combining blockchain technology with machine learning, which helps overcome major security flaws, including unauthorized access, data tampering, and insider threats.
Co-Authors Mohi uddin, K M