1 Department of AIML, Aditya University, Surempalem, India.
2 Department of CSE, Manipur International University, Imphal, India.
3 Department of C&IT, J.N.N. Institute of Engineering, Chennai, India.
International Journal of Science and Research Archive, 2025, 17(02), 570-573
Article DOI: 10.30574/ijsra.2025.17.2.3077
Received on 07 October 2025; revised on 13 November 2025; accepted on 15 November 2025
Data is the new currency as lot of the user’s presence online is an upward trend. As a consequence the data storage on the various cloud platforms has been a new normal. Data security in cloud has turn formidable due to unique security issues and challenges. Conventional methods on security may not always cater a proper barter between computational efficiency and data security. This review paper discusses the blending facial key features of the face obtained from VGG19 deep learning with homomorphic encryption to enrich cloud data security. The VGG19 allows for robust feature extraction from face and facial key points for authentication, while homomorphic encryption scales computation in encrypted form; it acquire enhanced accuracy with scalability and preservation of privacy. Thus, this method ensure a better approach in next-generation cloud security frameworks.
Cloud security; CNN; VGG16.VGG19; Facial key features
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Tadi. Chandrasekhar, Th. Basanta and J.N. Swaminathan. Review on Cloud Data Security Using VGG19-Deep Learning and Homomorphic Encryption. International Journal of Science and Research Archive, 2025, 17(02), 570-573. Article DOI: https://doi.org/10.30574/ijsra.2025.17.2.3077.
Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0
