**5. Conclusions**

The set of the options depends on the type of the concept, but in most cases its name is specified with description, as well as its current state. In the case when the weights of all connections, pointing to the concept, are assumed to be equal, one can mark the option "Imposed weight" and set the desired value. For countermeasures, it is permissible to indicate which of existing countermeasure it is, that allows realizing situations when one countermeasure acts on several connections at once. To establish the relationships between the concepts, it is necessary to click on the button "Placement" of the action group "Connections" in the tool window. After that, the connections are located by pressing consecutively on the initial and final element. The located countermeasures and initial states of the concepts can be adjusted and combined, creating the different scenarios that allow us to compare

**Figures 10** and **11** show the FGCM risk estimates built in the "Cognitive Map

Thus, the developed software "Cognitive Map Constructor" allows evaluating the effectiveness of the use of the TMI integrity monitoring system in the protection

*FGCM for risk assessment of data collection and storage subsystem at the service stations (Zone 1) (software*

*FGCM for risk assessment in the core of the CIN (Zone 2) and TMI (software window form).*

of telemetric information from the effects of external and internal threats.

the effectiveness of countermeasures.

Constructor."

*Digital Forensic Science*

**Figure 10.**

**Figure 11.**

**34**

*window form).*

A promising way to solve the problem of assessing the cybersecurity risks of industrial automated systems is to model the threats realization scenarios using the tools of topological analysis of the system security and cognitive modeling with the aid of Fuzzy Grey Cognitive Maps.

At the basis of this approach, the construction of original FGCM is proposed to assess the risk of automated control system with the following decomposition of FGCM into the number of cognitive maps of the next level of detail (the same as it is done in IDEF0 Functional Modeling technology). The features of construction of this procedure are discussed in this chapter in relation to the task of ensuring the telemetry information integrity in the industrial automated system for collecting, storing, and processing information on the conditions of on-board aviation systems. It is shown that the use of FGCM allows us to obtain more reliable estimates of security risk factors with account of the possible variations of the available actual data and expert opinions.

To automate the proposed risk assessment procedure in the considered system for collecting, storing, and processing telemetry information with use of FGCM, the software tool "Cognitive Map Constructor" was developed, which can be used for identifying the most dangerous vulnerabilities in the system and evaluating the effectiveness of various measures (countermeasures) realization for telemetric information protection from the impact of external and internal threats.
