Secure Data Exchange in the Industrial Internet of Things Network of the Fuel and Energy Complex

The issues of data exchange security increasing in the Industrial Internet of Things network of the fuel and energy complex enterprises based on the use of the domestic cryptographic protocol CRISP 1.0 are considered. A model example of industrial network infrastructure is analyzed and a fuzzy gray cognitive map is constructed to analyze local relative cybersecurity risks in the event of an internal attacker without using and using CRISP 1.0 as a protective measure. Indicators of local relative risk decreased by 35%. The use of cognitive analysis in the task of assessing cybersecurity risks allows us to take into account the spread of opinions of experts, as well as the inaccuracy and incompleteness of the data collected during the audit on the state and properties of the information system. Cognitive models make it possible to formalize the mutual influence of system elements and the destabilizing effects of internal and external attackers exploiting vulnerabilities of software and hardware components, and are an important decision support tool in the process of qualitative and quantitative risk assessments.