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Optimization Model of Adaptive Decision Taking Support System for Distributed Systems Cyber Security Facilities Placement

Kalizhanova Aliya, Akhmetov Sultan, Lakhno Valery, Wojcik Waldemar, Nabiyeva Gulnaz

International Journal of Electronics and Telecommunications

2020

Vol. 66, No. 3

493--498

An article herein presents an optimization model, designated for computational core of decision-taking support system (DTSS). DTSS is necessary for system analysis and search of optimal versions for cyber security facilities placement and information protection of an enterprise or organization distributed computational network (DCN). DTSS and a model allow automize the analysis of information protection and cyber security systems in different versions. It is possible to consider, how separate elements, influence at DCN protection factors and their combinations. Offered model, in distinction from existing, has allowed implementing both the principles of information protection equivalency to a concrete threat and a system complex approach to forming a highly effective protection system for DCN. Hereby we have presented the outcomes of computational experiments on selecting the rational program algorithm of implementing the developed optimization model. It has been offered to use genetic algorithm modification (GAM). Based on the offered model, there has been implemented the module for adaptive DTSS. DTSS module might be applied upon designing protected DCN, based on preset architecture and available sets of information protection and cyber security systems in the network.

Development of decision support system based on feature matrix for cyber threat assessment

Kartbayev Timur, Akhmetov Bakhytzhan, Doszhanova Aliya, Lakhno Valery, Malikova Feruza, Tolybayev Sharapatdin

International Journal of Electronics and Telecommunications

2019

Vol. 65, No. 4

545--550

The article herein presents the method and algorithms for forming the feature space for the base of intellectualized system knowledge for the support system in the cyber threats and anomalies tasks. The system being elaborated might be used both autonomously by cyber threat services analysts and jointly with information protection complex systems. It is shown, that advised algorithms allow supplementing dynamically the knowledge base upon appearing the new threats, which permits to cut the time of their recognition and analysis, in particular, for cases of hard-to-explain features and reduce the false responses in threat recognizing systems, anomalies and attacks at informatization objects. It is stated herein, that collectively with the outcomes of previous authors investigations, the offered algorithms of forming the feature space for identifying cyber threats within decisions making support system are more effective. It is reached at the expense of the fact, that, comparing to existing decisions, the described decisions in the article, allow separate considering the task of threat recognition in the frame of the known classes, and if necessary supplementing feature space for the new threat types. It is demonstrated, that new threats features often initially are not identified within the frame of existing base of threat classes knowledge in the decision support system. As well the methods and advised algorithms allow fulfilling the time-efficient cyber threats classification for a definite informatization object.