Applied Artificial Intelligence (Dec 2021)

Enhancing the Time Performance of Encrypting and Decrypting Large Tabular Data

  • Nguyen Thon Da,
  • Ho Trung Thanh

DOI
https://doi.org/10.1080/08839514.2021.1991661
Journal volume & issue
Vol. 35, no. 15
pp. 1746 – 1754

Abstract

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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.