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
- Arenlila Jamir, Sangeeta Kharde, Anita Dalal, Health-seeking behavior of first-time mothers toward pregnancy , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- B. Kalpana, P. Krishnamoorthy, S. Kanageswari, Anitha J. Albert, Machine learning approaches for predicting species interactions in dynamic ecosystems , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Roshni Kanth, R Guru, Anusuya M A, Madhu B K, A comprehensive study of AI in test case generation: Analysing industry trends and developing a predictive model , The Scientific Temper: Vol. 16 No. Spl-1 (2025): The Scientific Temper
- M. Monika, J. Merline Vinotha, A resilient supply chain model integrating demand variability and carbon emissions in imperfect production systems , The Scientific Temper: Vol. 16 No. 08 (2025): The Scientific Temper
- T. V. SATHE, BIODIVERSITY OF ICHNEUMONID FLIES (HYMENOPTERA : ICHNEUMONIDAE) FROM WESTERN GHATS, MAHARASHTRA , The Scientific Temper: Vol. 3 No. 1&2 (2012): The Scientific Temper
- Rama Shankar Dubey, M.A. Naidu, Ajay Kumar Shukla, Awadhesh Kumar Shukla, Manish Kumar, Sonia Verma, Pramod Kumar Mourya, Application of Bioactive Molecules in the Treatment and Management of Type-1 Diabetic Disease , The Scientific Temper: Vol. 13 No. 02 (2022): The Scientific Temper
- N.S.G. Ganesh, V Arulkumar, R. Lathamanju, Priscilla Joy , Energetic and highly reliable photovoltaic power source assisted water pump control system design using IoT , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- Prerna Khanna, Satinder Kumar, Exploring the expansion trajectory of the Indian automobile sector , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Rajeev P. R., K. Aravinthan, A novel approach for metrics-based software defect prediction using genetic algorithm , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Anita Mathew, Sneha Kanade, Fostering safe and inclusive workplace toward a sustainable and high-performing work culture , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
<< < 31 32 33 34 35 36 37 38 39 40 > >>
You may also start an advanced similarity search for this article.

