Ensuring privacy and confidentiality of cloud data: A comparative analysis of diverse cryptographic solutions based on run time trend.

Autor: Dawson JK; Sunyani Technical University, Sunyani, Ghana.; Kwame Nkrumah University of Science and Technology, Kumasi, Ghana., Frimpong T; Kwame Nkrumah University of Science and Technology, Kumasi, Ghana., Hayfron Acquah JB; Kwame Nkrumah University of Science and Technology, Kumasi, Ghana., Missah YM; Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.
Jazyk: angličtina
Zdroj: PloS one [PLoS One] 2023 Sep 07; Vol. 18 (9), pp. e0290831. Date of Electronic Publication: 2023 Sep 07 (Print Publication: 2023).
DOI: 10.1371/journal.pone.0290831
Abstrakt: The cloud is becoming a hub for sensitive data as technology develops, making it increasingly vulnerable, especially as more people get access. Data should be protected and secured since a larger number of individuals utilize the cloud for a variety of purposes. Confidentiality and privacy of data is attained through the use of cryptographic techniques. While each cryptographic method completes the same objective, they all employ different amounts of CPU, memory, throughput, encryption, and decryption times. It is necessary to contrast the various possibilities in order to choose the optimal cryptographic algorithm. An integrated data size of 5n*102 (KB (∈ 1,2,4,10,20,40) is evaluated in this article. Performance metrics including run time, memory use, and throughput time were used in the comparison. To determine the effectiveness of each cryptographic technique, the data sizes were run fifteen (15) times, and the mean simulation results were then reported. In terms of run time trend, NCS is superior to the other algorithms according to Friedman's test and Bonferroni's Post Hoc test.
Competing Interests: The authors have declared that no competing interests exist.
(Copyright: © 2023 Dawson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
Databáze: MEDLINE
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