Da, Nguyen Thon and Thanh, Ho Trung (2021) Enhancing the Time Performance of Encrypting and Decrypting Large Tabular Data. Applied Artificial Intelligence, 35 (15). pp. 1746-1754. ISSN 0883-9514
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Abstract
In the field of data analysis, encrypting and decrypting datasets must keep the information confidential. Currently, encrypting sizable tabular datasets is time-consuming. This study proposes a solution that helps encrypt extensive tabular data in lesser time than that required in conventional methods while preserving data analysis information. We use the feature by which a large dataset can be split into many files in hdf5 format and choose an encrypted algorithm to solve it. The study contributed to information technology knowledge management. We introduce a solution for small-scale companies to encrypt their extensive tabular data economically. The experimental results on three large datasets showed that our solution has a processing time between 1.2–5 times faster than the conventional processing time under some specific situations. The research results assist companies or individuals with a limited financial capacity to deploy data security and analysis at a low cost with time efficiency. The study opens several research opportunities in protecting large datasets and analyzing them in less time.
Item Type: | Article |
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Subjects: | STM Repository > Computer Science |
Depositing User: | Managing Editor |
Date Deposited: | 05 Jul 2023 04:02 |
Last Modified: | 21 Nov 2023 05:33 |
URI: | http://classical.goforpromo.com/id/eprint/3519 |