Simulation model of a fuzzy cyber attack detection system
| Autor: | Subach, Ihor, Fesokha, Vitalii, Mykytiuk, Artem, Kubrak, Volodymyr, Korotayev, Stanislav |
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| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | Scopus-Elsevier |
| DOI: | 10.5281/zenodo.7247964 |
| Popis: | The method of applying a simulation model of a fuzzy cyberattack detection system is considered. The functional diagram of the simulation model is given. The block diagram of the simulation model is considered and the purpose of its elements is described. The main steps of using a simulation model for conducting an experimental study of evaluating the effectiveness of models and methods for detecting cyber attacks based on the theory of fuzzy sets and fuzzy inference are described. The procedure for generating initial data is given, the classes of cyberattacks to be detected are defined, the vectors of cyberattack features are identified, the parameters of the studied traffic are described, the types of membership functions are defined to formalize expert knowledge and represent it in the knowledge base in the form of fuzzy production rules. The issue of parametric adaptation of membership functions to clarify the subjective judgments of experts are considered. To implement the possibility of detecting polymorphic cyberattacks, the procedure for determining the required number of the most important features for each known class of cyberattacks, represented by fuzzy sets and linguistic variables that characterize them quite fully, is described. A comparative analysis of the results of modeling the process of detecting cyber attacks based on the proposed approach with existing methods for detecting cyber attacks was carried out, based on the theory of fuzzy sets and fuzzy logic, artificial immune systems and neural networks in terms of accuracy. {"references":["Information Technologies and Security : Selected Papers of the XXI International Scientific and Practical Conference \"Information Technologies and Security\" (ITS 2021) (Kyiv, Ukraine, December 9, 2021): 3241. Aachen, Germany : CEUR Workshop Proceedings pp. 92–101."]} |
| Databáze: | OpenAIRE |
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