ECDS: Enhanced Cloud Data Security Technique to Protect Data Being Stored in Cloud Infrastructure
Data Security in Cloud Infrastructure
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2024.15.4.19Keywords:
Cloud computing security, Data protection, Cryptographic, Symmetric encryption, Data encryptionDimensions 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.
The rapid adoption of cloud computing has transformed IT resource management by providing scalable, flexible, and cost-effective solutions. Despite these benefits, cloud computing presents critical security challenges, particularly in protecting sensitive data during transmission and storage. This paper introduces the Enhanced Cloud Data Security (ECDS) technique, a new approach aimed at strengthening data protection within cloud infrastructures. ECDS incorporates substitution and permutation methods to secure data and utilizes a combination of encryption strategies to ensure that encrypted data remains inaccessible to unauthorized users. ECDS is a symmetric cryptographic system that uses the same key for encryption and decryption. It is 256-bit block cipher encryption and it uses 312-but keys. The ECDS is implemented in Python and compared against DES and Blowfish Encryption techniques. Extensive testing and performance analysis reveal that ECDS significantly enhances security and efficiency compared to traditional encryption methods. This paper contributes to the ongoing efforts to secure cloud computing environments for safeguarding sensitive data in the cloud.Abstract
How to Cite
Downloads
Similar Articles
- Neeraj, Anita Singhrova, A critical review of blockchain-based authentication techniques , The Scientific Temper: Vol. 16 No. 04 (2025): The Scientific Temper
- A. Sathya, M. S. Mythili, MOHCOA: Multi-objective hermit crab optimization algorithm for feature selection in sentiment analysis of Covid-19 Twitter datasets , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- M. Iniyan, A. Banumathi, The WBANs: Steps towards a comprehensive analysis of wireless body area networks , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Shantanu Kanade, Anuradha Kanade, Secure degree attestation and traceability verification based on zero trust using QP-DSA and RD-ECC , The Scientific Temper: Vol. 15 No. spl-2 (2024): The Scientific Temper
- Amit Maru, Dhaval Vyas, Hybrid deep learning approach for pre-flood and post-flood classification of remote sensed data , The Scientific Temper: Vol. 16 No. Spl-1 (2025): The Scientific Temper
- Bommaiah Boya, Premara Devaraju, Integrating clinical and ECG data for heart disease prediction: A hybrid deep learning approach based on two modalities with particle swarm optimization , The Scientific Temper: Vol. 16 No. 05 (2025): The Scientific Temper
- J. Helan Shali Margret, N. Amsaveni, A study on recency patterns of cited resources in the cytokine publications from web of science , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Hannah Ayaba Tanye, Henry Akwetey Matey, Isaac Asampana, Albert Akanlisikum Akanferi, Douglas Yeboah , Augustina Dede Agor, Assessing the information security awareness among Ghanaian University students , The Scientific Temper: Vol. 16 No. 07 (2025): The Scientific Temper
- Neeraj ., Anita Singhrova, Quantum Key Distribution-based Techniques in IoT , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Pravin P. P, J. Arunshankar, Development of digital twin for PMDC motor control loop , The Scientific Temper: Vol. 14 No. 01 (2023): The Scientific Temper
<< < 4 5 6 7 8 9 10 11 12 13 > >>
You may also start an advanced similarity search for this article.

