Enhancing the Time Performance of Encrypting and Decrypting Large Tabular Data
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 metho...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2021-12-01
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| Series: | Applied Artificial Intelligence |
| Online Access: | http://dx.doi.org/10.1080/08839514.2021.1991661 |
| Summary: | 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. |
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| ISSN: | 0883-9514 1087-6545 |