Cost-effective privacy preserving of intermediate data using group search optimisation algorithm

G. Jaikrishna and Sugumar Rajendran

International Journal of Business Information Systems, 2020, vol. 35, issue 2, 132-151

Abstract: Cloud computing provides huge storage ability to clients, in order to convey their applications without any infrastructure investment. Alongside those applications, an extensive set of intermediate datasets will be created, and it is a challenging issue to protect the security of those intermediate datasets. Therefore, in this paper, we preserve only sensitive information which reduces the time and cost. For privacy preserving of the intermediate dataset, in this paper, we propose a combination of group search optimisation (GSO) and advanced encryption standard (AES). At first, the original dataset is split into an intermediate dataset and we select the corresponding node from the cloud for each intermediate dataset using GSO algorithm. After that, we separate the sensitive data using information gain. Finally, we apply the AES to encrypt the sensitive data. The performance of proposed methodology is in terms of encryption time and memory usage.

Keywords: cloud computing; group search optimisation; GSO; advanced encryption technique standard; information gain; intermediate data and sensitive data. (search for similar items in EconPapers)
Date: 2020
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