Electronic footprint analysis and cluster analysis techniques for information security risk research of university digital systems


  • Valerii Lakhno National University of Life and Environmental Sciences of Ukraine
  • Myroslav Lakhno National University of Life and Environmental Sciences of Ukraine
  • Kaiyrbek Makulov Caspian University of Technology and Engineering named after Sh.Yesenova
  • Olena Kryvoruchko State University of Trade and Economics
  • Alona Desiatko State University of Trade and Economics
  • Vitaliy Chubaievskyi State University of Trade and Economics
  • Dmytro Ishchuk Zhytomyr Politechnic State University
  • Viktoriya Kabylbekova Caspian University of Technology and Engineering named after Sh.Yesenova


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 university's DEE.


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Cryptography and Cybersecurity