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

John Kwao Dawson, Twum Frimpong, James Benjamin Hayfron Acquah and Yaw Marfo Missah

PLOS ONE, 2023, vol. 18, issue 9, 1-15

Abstract: 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.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0290831

DOI: 10.1371/journal.pone.0290831

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