Electronic footprint analysis and cluster analysis techniques for information security risk research of university digital systems
Lakhno V. Lakhno M. Makulov K. Kryvoruchko O. Desiatko A. Chubaievskyi V. Ishchuk D. Kabylbekova V.
20 June 2024Polska Akademia Nauk
International Journal of Electronics and Telecommunications
2024#70Issue 2405 - 412 pp.
In the article there are presented results of the study of the state of user competencies for different specialties of the university digital educational environment (UDEE) on issues related to information security (IS). The methods of cluster analysis and analysis of digital (electronic) traces (DT) of users are used. On the basis of analyzing the DTs of different groups of registered users in the UDEE, 6 types of users are identified. These types of users were a result of applying hierarchical classification and k-means method. Users were divided into appropriate clusters according to the criteria affecting IS risks. For each cluster, the UDEE IS expert can determine the probability of occurrence of high IS risk incidents and, accordingly, measures can be taken to address the causes of such incidents. The algorithms proposed in this study enable research during log file analysis aimed at identifying breaches of information security within the universitys DEE.
cluster analysis , digital footprints , hierarchical classification , information security , k-means method , risks , university digital educational environment
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National University of Life and Environmental Sciences of Ukraine, Kyiv, Ukraine
Caspian University of Technology and Engineering named after Sh.Yesenova, Almaty, Kazakhstan
State University of Trade and Economics, Kyiv, Ukraine
Zhytomyr Politechnic State University, Zhytomyr, Ukraine
National University of Life and Environmental Sciences of Ukraine
Caspian University of Technology and Engineering named after Sh.Yesenova
State University of Trade and Economics
Zhytomyr Politechnic State University
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