Enhancing the Time Performance of Encrypting and Decrypting Large Tabular Data

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
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

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