Published Online: Dec 26, 2023
Page range: 40 - 44
Received: Jan 11, 2022
Accepted: Sep 07, 2022
DOI: https://doi.org/10.14313/jamris/1-2023/5
Keywords
© 2023 Marcin Kujawa et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
The article presents an approach to data anonymization with the use of generally available tools. The focus is put on the practical aspects of using open-source tools in conjunction with programming libraries provided by suppliers of industrial control systems. This universal approach shows the possibilities of using various operating systems as a platform for process data anonymization. An additional advantage of the described approach is the ease of integration with various types of advanced data analysis tools based both on the out-of-the-box approach (e.g., business intelligence tools) as well as customized solutions. The discussed case describes the anonymization of data for the needs of sensitive analysis by a wider group of recipients during the construction of a predictive model used to support decisions.