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

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


Abstract— 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 cybersecurity 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 cybersecurity 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 cybersecurity systems in the network.

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Avgerou, C., & Walsham, G. (Eds.). (2017). Information technology in context: Studies from the perspective of developing countries: Studies from the perspective of developing countries. Routledge.

Clarkson, A. (2019). Toward effective strategic analysis: new applications of information technology. Routledge.

Grabowski, M., & Roberts, K. H. (2019). Reliability seeking virtual organizations: Challenges for high reliability organizations and resilience engineering. Safety science, 117, 512-522.

Sabi, H. M., Uzoka, F. M. E., Langmia, K., & Njeh, F. N. (2016). Conceptualizing a model for adoption of cloud computing in education. International Journal of Information Management, 36(2), 183-191.

Zadeh, A. H., Akinyemi, B. A., Jeyaraj, A., & Zolbanin, H. M. (2018). Cloud ERP Systems for Small-and-Medium Enterprises: A Case Study in the Food Industry. Journal of Cases on Information Technology (JCIT), 20(4), 53-70.

Wang, K., Zhang, Y., Guo, S., Dong, M., Hu, R. Q., & He, L. (2018). IEEE Access Special Section Editorial: The Internet of Energy: Architectures, Cyber Security, and Applications. IEEE access, 6, 79272-79275.

Deng, S., Zhou, A. H., Yue, D., Hu, B., & Zhu, L. P. (2017). Distributed intrusion detection based on hybrid gene expression programming and cloud computing in a cyber physical power system. IET Control Theory & Applications, 11(11), 1822-1829.

Sallam, H. (2015). Cyber security risk assessment using multi fuzzy inference system. IJEIT, 4(8), 13-19.

Alali, M., Almogren, A., Hassan, M. M., Rassan, I. A., & Bhuiyan, M. Z. A. (2018). Improving risk assessment model of cyber security using fuzzy logic inference system. Computers & Security, 74, 323-339.

Erdogmus, D., & Principe, J. C. (2002). Generalized information potential criterion for adaptive system training. IEEE Transactions on Neural Networks, 13(5), 1035-1044.

Akhmetov, B., Lakhno, V., Akhmetov, B., & Alimseitova, Z. (2018, September). Development of sectoral intellectualized expert systems and decision making support systems in cybersecurity. In Proceedings of the Computational Methods in Systems and Software (pp. 162-171). Springer, Cham.

Zhang, Peng, et al. Pattern mining model based on improved neural network and modified genetic algorithm for cloud mobile networks. Cluster Computing, 2019, 22.4: 9651-9660.

Lakhno, V., Tsiutsiura, S., Ryndych, Y., Blozva, A., Desiatko, A., Usov, Y., & Kaznadiy, S. (2019). Optimization of information and communication transport systems protection tasks. International Journal of Civil Engineering and Technology, 10(1), 2019.


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