Contextual Characteristics of Digital Footprints and Their Impact on University Information Security

For the studied area of information security management (ISM) of the university information and educational environment (IEE), it is shown that the effective use of data obtained by collecting and analyzing various digital footprints (DF) of users, including students, teachers and staff, is possible to increase the level of ISM and the degree of its protection against external and internal threats. A conceptual model of a decision support system (DSS) module based on the analysis of IOSS users' CS is developed. The model takes into account both context-dependent and context-independent characteristics of the CA (respectively, CCA, CCA) that affect the state of the IS in the IIS. The analysis of CS within the IES provides university IS specialists with the opportunity not only to determine the levels of competence and track individual educational trajectories of students, but also to develop appropriate controlling influences to ensure the sustainability of IS. We consider the use of software products such as Splunk and ELK Stack (which includes Elasticsearch, Logstash, and Kibana), which allow not only to effectively analyze but also to identify potential threats to IES. These tools provide universities with high efficiency in identifying, tracking and analyzing problems related to user's CA, thereby contributing to improved protection against unauthorized access to IPS resources.