Vol.14, No.2, May 2025.                                                                                                                                                                          ISSN: 2217-8309

                                                                                                                                                                                                                        eISSN: 2217-8333

 

TEM Journal

 

TECHNOLOGY, EDUCATION, MANAGEMENT, INFORMATICS

Association for Information Communication Technology Education and Science


Advancing User Authentication in Cloud Computing: Automated Smart Application as a Multi-Factor Approach Beyond Extended-Levenshtein Distance

 

Boumedyen Shannaq

 

© 2025 Boumedyen Shannaq, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)

 

Citation Information: TEM Journal. Volume 14, Issue 2, Pages 1140-1151, ISSN 2217-8309, DOI: 10.18421/TEM142-15, May 2025.

 

Received: 16 September 2024.

Revised:  03 March 2025.
Accepted: 18 April 2025.
Published: 27 May 2025.

 

Abstract:

 

This research aims to unveil the area of user authentication in cloud computing. The study aims to investigate an algorithm known as the ‘Confidence Range’ (CR) algorithm, which was introduced in cloud computing to address its limitations and reduce discrepancies in password security. The CR algorithm creates individual EPSBs for password-authorized users, allowing password activity to be monitored and helping them remember their passwords. Additionally, password activity can be monitored to identify anomalies. However, as a result, this work identified a loophole in the CR algorithm, precisely when the same password is used in different positions. To address this vulnerability, this work introduces a new algorithm. The extended algorithm also shows promising results compared to the CR and Levenshtein Distance algorithms. However, the weaknesses of the Confidence Range algorithm are revealed in the second experiment: Its ability to distinguish between fake and genuine users is low, with a recognition precision rate of only 2.94%. Levenshtein Distance algorithm promises a precision of 19, on the other hand, 11%, and the precision of the Levenshtein Distance with the Confidence Range algorithm expanded is 27. 94%. These results suggest a need for continuous improvement and assessment of authentication security in cloud computing, where Confidence Range approaches offer potential enhancements to password protection systems. Further studies are needed to explore alternative strategies and to improve password protection systems in real-world contexts.

 

Keywords – Authentication, CR algorithm, multi-factor, Levenshtein Distance, innovative information security application

 

-----------------------------------------------------------------------------------------------------------

Full text PDF >  

-----------------------------------------------------------------------------------------------------------

 


Copyright © 2025 UIKTEN
Copyright licence: All articles are licenced via Creative Commons CC BY-NC-ND 4.0 licence