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Research Paper
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Paper Title

Machine Learning and Deep Learning Based Approach to Secure Cloud Computing Paradigm

Article Identifiers

Registration ID: IJNRD_220294

Published ID: IJNRD2404892

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Keywords

Cloud computing, machine learning, deep learning, data encryption etc.

Abstract

In this paper we explains the relationship between machine learning (ML) and cloud computing (CC), emphasizing the problems, opportunities, and solutions. It displays the ways that cloud computing (CC) has changed the Internet service industry as well as the financial effects with data collection and analysis. In particular, security concerns in distributed models are discussed, and edge computing—a cloud computing (CC) variant meant for data that must be processed quickly—is introduced. The distribution of rights, data encryption, and the transfer of data accountability from providers of services to end users are all covered in this essay. The paper addresses security concerns with integrity, availability, and threat identity by dissecting cloud computing across service and delivery architectures. It proposes machine learning (ML) methods as a remedy for data quality control and security. The difficulties in integrating Cloud Computing (CC) and machine learning (ML), such as data interchange latency, scalability optimization, model deployment, management of resources, data security and monitoring, are highlighted in this study. A strategy for educating businesses about cloud computing (CC) and machine learning (ML) is offered. The final section of the summary emphasizes how cloud computing (CC) and deep learning, as well as machine learning (ML) are evolving to influence computing and analytics in the future and increase an organization's competitiveness in the digital era

How To Cite (APA)

SANGEETA DEVI, MUNISH SARAN, PRANJAL MAURYA, RAJAN KUMAR YADAV, & UPENDRA NATH TRIPATHI (April-2024). Machine Learning and Deep Learning Based Approach to Secure Cloud Computing Paradigm. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), i832-i840. https://ijnrd.org/papers/IJNRD2404892.pdf

Issue

Other Publication Details

Paper Reg. ID: IJNRD_220294

Published Paper Id: IJNRD2404892

Downloads: 000122254

Research Area: Computer Science & Technology 

Author Type: Indian Author

Country: GORAKHPUR, UTTAR PRADESH, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404892.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404892

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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

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Call For Paper

Call For Paper - Volume 10 | Issue 12 | December 2025

IJNRD is a Scholarly Open Access, Peer-Reviewed, Refereed, and UGC CARE Journal Publication with a High Impact Factor of 8.76 (calculated by Google Scholar & Semantic Scholar | AI-Powered Research Tool). It is a Multidisciplinary, Monthly, Low-Cost, and Transparent Peer Review Journal Publication that adheres to the UGC CARE 2025 Peer-Reviewed Journal Policy and aligns with Scopus Journal Publication standards to ensure the highest level of research quality and credibility.

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Important Dates for Current issue

Paper Submission Open For: December 2025

Current Issue: Volume 10 | Issue 12 | December 2025

Impact Factor: 8.76

Last Date for Paper Submission: Till 31-Dec-2025

Notification of Review Result: Within 1-2 Days after Submitting paper.

Publication of Paper: Within 01-02 Days after Submititng documents.

Frequency: Monthly (12 issue Annually).

Journal Type: IJNRD is an International Peer-reviewed, Refereed, and Open Access Journal with Transparent Peer Review as per the new UGC CARE 2025 guidelines, offering low-cost multidisciplinary publication with Crossref DOI and global indexing.

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