ETTG: Enhanced token and tag generation for authenticating users and deduplicating data stored in public cloud storage
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2024.15.3.18Keywords:
Cloud Storage, Data Deduplication, Token Generation, Cryptographic Techniques, Computation EfficiencyDimensions Badge
Issue
Section
License
Copyright (c) 2024 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
As cloud storage services continue to grow in popularity, the need for secure and efficient data management has become paramount. Public cloud storage offers benefits such as cost efficiency, scalability, and accessibility, but it also presents significant challenges related to data security and storage optimization. To address these challenges, the paper proposes an Enhanced Token and Tag Generation (ETTG) technique designed to improve data deduplication in public cloud storage. ETTG utilizes advanced cryptographic methods to generate secure tokens and tags, ensuring robust, efficient deduplication processes. The comprehensive evaluation demonstrates that ETTG significantly reduces computation time compared to existing techniques, making it particularly suitable for data-intensive cloud environments. By minimizing redundant data and enhancing data security, ETTG not only optimizes storage utilization but also improves overall system performance. This paper details the design and implementation of ETTG, its evaluation against existing methods, and its potential impact on the efficiency and security of cloud storage services.Abstract
How to Cite
Downloads
Similar Articles
- S. Prabagar, Vinay K. Nassa, Senthil V. M, Shilpa Abhang, Pravin P. Adivarekar, Sridevi R, Python-based social science applications’ profiling and optimization on HPC systems using task and data parallelism , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- V. Baby Deepa, R. Jeya, Dynamic resource allocation with otpimization techniques for qos in cloud computing , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- K. Vani, S. Sujatha, Fault tolerance systems in open source cloud computing environments–A systematic review , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Balaji V, Purnendu Bikash Acharjee, Muniyandy Elangovan, Gauri Kalnoor, Ravi Rastogi, Vishnu Patidar, Developing a semantic framework for categorizing IoT agriculture sensor data: A machine learning and web semantics approach , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- Ellakkiya Mathanraj, Ravi N. Reddy, Enhanced principal component gradient round-robin load balancing in cloud computing , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- D. Jayadurga, A. Chandrabose, Expanding the quantity of virtual machines utilized within an open-source cloud infrastructure , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- R. Prabhu, P. Archana, S. Anusooya, P. Anuradha, Improved Steganography for IoT Network Node Data Security Promoting Secure Data Transmission using Generative Adversarial Networks , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Dileep Pulugu, Shaik K. Ahamed, Senthil Vadivu, Nisarg Gandhewar, U D Prasan, S. Koteswari, Empowering healthcare with NLP-driven deep learning unveiling biomedical materials through text mining , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- Sheena Edavalath, Manikandasaran S. Sundaram, MARCR: Method of allocating resources based on cost of the resources in a heterogeneous cloud environment , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- S ChandraPrabha, S. Kantha Lakshmi, P. Sivaraaj, Data analysis and machine learning-based modeling for real-time production , The Scientific Temper: Vol. 14 No. 02 (2023): The Scientific Temper
<< < 1 2 3 4 5 6 7 8 9 10 > >>
You may also start an advanced similarity search for this article.
Most read articles by the same author(s)
- Olivia C. Gold, Jayasimman Lawrence, Ensemble of CatBoost and neural networks with hybrid feature selection for enhanced heart disease prediction , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper