Paper Title

Design and Analysis of Attribute based encryption Scheme for cloud security and privacy with machine learning

Article Identifiers

Registration ID: IJNRD_220757

Published ID: IJNRD2406058

DOI: Click Here to Get

Authors

Disha Jamdade , Kalpana Thakre , Swati Shekapure , Neha Jain

Keywords

Deep Neural Networks, Skin Lesion, Machine Learning.

Abstract

Encrypting shared resources in the cloud with ciphertext attribute-based encryption has shown to be a dependable method for ensuring their security and privacy. Malicious individuals, however, took advantage of weaknesses in sharing systems like master keys and access regulations. Furthermore, the many features of the cloud-based shared resource are utilized in the construction of the access control mechanisms. The computation of the master and secret keys, as well as the encryption and decryption processes, take longer the more characteristics there are. Observations on contributing qualities are a key factor to take into account when creating a machine learning model for improved accountability. In this study, we have presented a novel attribute-based encryption to offer enhanced security and better cloud access control. It would be more efficient to encrypt data at the data owner's cloud server using dynamic features to prevent key leaking. While the secret key is being produced at the proxy server, performance is improved. A good and promising performance is obtained, with the computation time being cut to about half of the existing methods. Additionally, the observations satisfy the necessary accountability requirements.

How To Cite (APA)

Disha Jamdade , Kalpana Thakre, Swati Shekapure, & Neha Jain (June-2024). Design and Analysis of Attribute based encryption Scheme for cloud security and privacy with machine learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(6), a613-a620. https://ijnrd.org/papers/IJNRD2406058.pdf

Issue

Volume 9 Issue 6, June-2024

Pages : a613-a620

Other Publication Details

Paper Reg. ID: IJNRD_220757

Published Paper Id: IJNRD2406058

Downloads: 000121984

Research Area: Engineering

Country: Karad, Maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2406058.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2406058

About Publisher

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

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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Call For Paper - Volume 10 | Issue 10 | October 2025

IJNRD is a Scholarly Open Access, Peer-reviewed, and Refereed Journal 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 Journal that follows UGC CARE 2025 Peer-Reviewed Journal Policy norms, Scopus journal standards, and Transparent Peer Review practices to ensure quality and credibility. IJNRD provides indexing in all major databases & metadata repositories, a citation generator, and Digital Object Identifier (DOI) for every published article with full open-access visibility.

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Important Dates for Current issue

Paper Submission Open For: October 2025

Current Issue: Volume 10 | Issue 10 | October 2025

Impact Factor: 8.76

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

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

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