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A statistical performance analysis of three double-layer homomorphic encryption schemes for cloud enterprise resource planning (ERP) data

Arnold Mashud AbukariEdem Kwedzo BankasAlhassan AbukariMohammed Muniru Iddrisu

Abstract

This study presented a statistical performance analysis of three double-layer homomorphic encryption schemes for cloud Enterprise Resource Planning (ERP) data. In this study, Abukari et al. (2021) proposed a hybrid of two homomorphic encryption scheme and compared with the state-of-the-art Usha (2018) and Bellafqira et al. (2017) double layer homomorphic encryption schemes using the combination of the RSA cryptographic algorithm and the modified Paillier cryptosystem in a hybrid approach. The Multivariate Analysis of Variance (MANOVA) was used to test whether the mean encryption times of the three schemes differ significantly across the data sizes as well as determine which encryption times among the three schemes have the largest difference for each of the data sizes. Preliminary analysis revealed that our new proposed scheme Abukari et al. (2021) has the lowest mean mean encryption times of 5.4150, 10.6570 and 39.9770 across the different data sizes of 7MB, 14MB and 200MB compared to the existing state-of-the-art Bellafqira et al. (2017) and Usha (2018). The MANOVA test revealed that there is a statistically significant difference in encryption times of the various schemes across the different data sizes, F (6, 52) = 8.827, p

Cryptography and Data SecurityCloud Data Security SolutionsChaos-based Image/Signal EncryptionHomomorphic encryptionEncryptionComputer scienceCloud computingCryptosystemCryptographyMultivariate analysis of varianceAlgorithmTheoretical computer scienceComputer security
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A statistical performance analysis of three double-layer homomorphic encryption schemes for cloud enterprise resource planning (ERP) data · Scinovex