ALGORITHM OF FORMING KNOWLEDGEBASE FOR DECISION TAKING SUPPORT SYSTEMS IN CYBER SECURITY TASKS

In the article herein, we offer the total structure of modular decision taking support system in cyber security tasks. There is described the model for fuzzy inference subsystem. Being based on the fuzzy inference rules on the input values, which can be obtained from the sensors, multiagent systems, SIEM systems, determining the threats availability, cyberattacks, anomalies, it has been proposed to specify output values for evaluating the critically important computer systems protection degree by means of decision taking support system. The model is based on the supposition, that input magnitudes for the fuzzy inference subsystems have been obtained as a result of fuzzification procedure in the corresponding module. Every element of output value characterizes the availability or absence of fuzzy situation signs, connected with anomalies, attacks or other attempts of unauthorized interference into the critically important computer systems operation. There is offeredan algorithm of forming the knowledgebase of fuzzy (emergency) and standard situations in the critically important computer systems. The algorithm differs from the known ones by the fact, that it has allowed forming the aggregate of standard variants cases for reacting at the threats, anomalies and attacks in the critically important computer systems, as well, inference rules for the fuzzy authentication, which are, first and foremost, linked with the task-oriented destructive impact at the critically important computer systems. Fuzzy logic inference module usage allows maintaining the display of the most vulnerable CICS's components condition as a multiparameter “image”. Obtained multiparameter “image” might be applied in the decision taking support system for the CICS protection qualitative assessment