Issue |
E3S Web Conf.
Volume 210, 2020
Innovative Technologies in Science and Education (ITSE-2020)
|
|
---|---|---|
Article Number | 11001 | |
Number of page(s) | 8 | |
Section | Environmental Planning and Policy | |
DOI | https://doi.org/10.1051/e3sconf/202021011001 | |
Published online | 04 December 2020 |
Theoretical aspects of the protection of personal data of employees of the enterprise by the method of pseudonymization
1 Don State Technical University, 344003, Gagarin sq., 1, Rostov on Don, Russia
2 Kazan state agrarian University, 420015, 65 K. Marx str., Kazan, Russia
3 Kazan (Volga region) Federal University, 420008, 18 Kremlevskaya str., Kazan, Russia
* Corresponding author: gazandre@yandex.ru
The topic of pseudonymization of personal data has shown, that theoretical and methodological basics in sphere of automatized systems have just started to gain general trend. The majority of studies in this sphere are, commonly, about personal data in general, rarely touching the topic of pseudonymization and depersonalization. Therefore, the topic of pseudonymization has not fully assimilated in enterprise systems and has not grown any popularity, because enterprises tend to choose reliable tools and methods of information security while depersonalization is only beginning its way and is not common for big corporations. This leads to disinterestedness in solving known issues and goals of pseudonymization, universal methods have not been researched. However, low cost and simplicity of this method of personal data protection is turning our attention on it and ask ourselves a question: “Should we have a deep dive in it?”. Answer is obvious – yes. Certainly, this method has its disadvantages and it is not an ideal solution. But it certainly should be distributed worldwide.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.