Enhancing cloud data security: User-centric approaches and advanced mechanisms
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2024.15.1.29Keywords:
Cloud storage, Encryption algorithms, Biometric authentication, Cloud data security, Security validation, Authentication success rate.Dimensions 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.
Cloud storage has led to a transformative era of data management for organizations, but this paradigm shift has also introduced critical security challenges. This paper is motivated by the urgent need to strengthen cloud data security against unauthorized access and breaches. Our investigation revolves around the vulnerabilities stemming from distributed links in cloud storage, shedding light on the paramount importance of safeguarding crucial commercial records. These challenges encompass the menace posed by both external attackers and unscrupulous customers, amplified within the complex landscape of multi-tenant architectures. This work presents the Secure-Cloud-Guard algorithm to achieve these goals—a multifaceted approach integrating encryption, biometric authentication, and MAC address security mechanisms. The Secure-Cloud-Guard algorithm, rooted in the user-centric paradigm, enhances data protection in cloud storage environments by orchestrating multiple layers of security. The algorithm’s simulation involves thorough evaluation through encryption performance analysis, biometric authentication testing, and MAC address security validation. The simulation results reveal the effectiveness of our proposed algorithm. Encryption performance metrics showcase the encryption throughput and latency, thereby gauging the efficiency of the encryption process. The biometric authentication simulation calculates the false acceptance rate (FAR) to determine the algorithm’s accuracy and false rejection rate (FRR). The simulation of MAC address security illustrates the algorithm’s ability to authenticate devices through MAC addresses, providing insights into its authentication success rate (ASR). In conclusion, an, aligning with user-centric approaches and incorporating advanced mechanisms, such as encryption, biometric authentication, MAC address security, contribute to the ongoing efforts of fortifying the security landscape of cloud storage and computingAbstract
How to Cite
Downloads
Similar Articles
- Dhulasi Priya S, Saranya K G, Significance of artificial intelligence in the development of sustainable transportation , The Scientific Temper: Vol. 14 No. 02 (2023): The Scientific Temper
- Kapil ahuja, Ekta Rani, Soniya Devi, Exploring the dynamic landscape of environmental, social, and governance literature by using bibliometric analysis , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Sirajum Munira Priety, Farhan Bin Manjur, AI Driven Approach in Smart Manufacturing in Bangladesh , The Scientific Temper: Vol. 16 No. 10 (2025): The Scientific Temper
- Radha K. Jana, Dharmpal Singh, Saikat Maity, Modified firefly algorithm and different approaches for sentiment analysis , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Chinnadurai U, A. Vinayagam, Energy efficient routing with cluster approach in wireless networks – A literature review , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Rudrapati Bhuvaneswara Prasad, Avutala Mallikarjuna Reddy, Edge properties of lexicographic product graphs of open neighborhood graphs , The Scientific Temper: Vol. 16 No. 01 (2025): The Scientific Temper
- Farheen Najma B, Faseeha Begum, Resistance to digital banking by senior citizens in India - A review , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Deepesh Bhardwaj, Niyati Chaudhary, Blueprints of Green: Determining Key Determinants of Sustainable Real Estate Projects in Delhi NCR , The Scientific Temper: Vol. 17 No. 01 (2026): The Scientific Temper
- Gomathi Ramalingam, Logeswari S, M. D. Kumar, Manjula Prabakaran, Neerav Nishant, Syed A. Ahmed, Machine learning classifiers to predict the quality of semantic web queries , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Vijaykumar S. Kamble, Prabodh Khampariya, Amol A. Kalage, Application of optimization algorithms in the development of a real-time coordination system for overcurrent relays , The Scientific Temper: Vol. 14 No. 01 (2023): The Scientific Temper
<< < 19 20 21 22 23 24 25 26 27 28 > >>
You may also start an advanced similarity search for this article.
Most read articles by the same author(s)
- J. M. Aslam, K. M. Kumar, Enhancing security of cloud using static IP techniques , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper

