Auditing of information security constitutes a key part of security operations taken inside organizations. Often information security problems must be addressed as quickly as possible. The purposes of this work are to provide an insight to information security management and suggest some of solutions of developing expert system. This paper discusses the development of an application, which is based on international standards on information security and protection tools. The expert system is accompanied by web-based application module, which serves as an instrument for solving various security-related problems.

The paper presents a mathematical model integrated into the computational core of a decision support system (DSS) for the selection of cloud platforms under conditions of fuzzy information. The model facilitates the development of rational strategies for players’ interaction with cloud platforms, allowing to balance investment, security and quality of services provided. This study proposes a methodology for determining optimal strategies in cloud platform selection using a differential quality game under fuzzy conditions, taking into account their preferences and opportunities to use technologies related to the analysis of user activities, i.e., digital footprints. The performed computational experiments confirmed the effectiveness of the model and allowed us to visualize the results of the interaction based on synthetic data. The results of the study may be useful to analysts dealing with cloud solution selection problems under uncertainty and cybersecurity needs. The relevance of the study is due to the global trend of business processes moving to the cloud and the increasing requirements for data security in the digitalization of the economy, which makes the choice of an optimal cloud platform strategically significant. Employing a differential quality game with fuzzy information, this study introduces a reliable DSS that incorporates cost, security and QoS to select the most appropriate cloud platform. The computational experiments validate the model in reproducing plausible interactions yielding relevant insights for decision-makers.

A methodology for evaluating information security (IS) for a distributed computer network (DCN) of a university (hereinafter referred to as UDCN) has been proposed. A mathematical model for calculating the UDCN vulnerability factor has been presented. The UDCN vulnerability coefficient makes it possible to assess its IS level at the UDCN design stage. The results of simulation modeling and virtualization of IS UDCN components have also been presented. In the course of simulation modeling, a model of a protected UDCN was designed and tested. In the experimental UDCN model, the network devices selected in the course of modeling the vulnerability coefficient were emulated on virtual machines (VMs). UDCN resources were reproduced using the Proxmox VE virtualization system. On the UDCN hosts running PVE, the Suricata Intrusion Detection System (IPS) was used. Splunk was used as SIEM.