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Документ Automated penetration testing method using deep machine learning technology(Національний технічний університет "Харківський політехнічний інститут", 2021) Semenov, Serhii; Weilin, Cao; Liqiang, Zhang; Bulba, SerhiiThe article developed a method for automated penetration testing using deep machine learning technology. The main purpose of the development is to improve the security of computer systems. To achieve this goal, the analysis of existing penetration testing methods was carried out and their main disadvantages were identified. They are mainly related to the subjectivity of assessments in the case of manual testing. In cases of automated testing, most authors confirm the fact that there is no unified effective solution for the procedures used. This contradiction is resolved using intelligent methods of analysis. It is proposed that the developed method be based on deep reinforcement learning technology. To achieve the main goal, a study was carried out of the Shadov system's ability to collect factual data for designing attack trees, as well as the Mulval platform for generating attack trees. A method for forming a matrix of cyber intrusions using the Mulval tool has been developed. The Deep Q - Lerning Network method has been improved for analyzing the cyber intrusion matrix and finding the optimal attack trajectory. In the study, according to the deep reinforcement learning method, the reward scores assigned to each node, according to the CVSS rating, were used. This made it possible to shrink the attack trees and identify an attack with a greater likelihood of occurring. A comparative study of the automated penetration testing method was carried out. The practical possibility of using the developed method to improve the security of a computer system has been revealed.Документ Research of the software security model and requirements(Національний технічний університет "Харківський політехнічний інститут", 2021) Semenov, Serhii; Davydov, Viacheslav; Hrebeniuk, DarynaThe subject of research in the article is a software security model. The aim of the work is to research the quality characteristics of the software and requirements for the software security in order to improve their safety. The article solves the following tasks: researching the shortcomings of the existing security model in order to identifyits main shortcomings; study of the quality characteristics of software that affect its security in order to identify the possibility of improving the quality of software. The following results were obtained: on the basis of the analysis of the existing model of software security, the main features of the attributes of this model were identified, their advantages and disadvantages were given. On the basis of the conducted analytical study, the necessity of improving the existing model of ensuring the security of software has been proved. Existing requirements for software and characteristics that affect its quality are considered. The characteristics of software security are highlighted, the indicators of which should be improved. Conclusions: a software security model has been studied. The need to develop this model is shown by introducing the possibility of adapting the existing requirements for the security of software tools throughout the entire life cycle of software development; the study of the quality characteristics of software showed that to ensure its security, it is necessary to improve the following characteristics: integrity, authentication, confidentiality, access control. However, it was shown that an increase in these characteristics can lead to a deterioration in other indicators of software quality: portability, maintainability, performance.Документ Testing process for penetration into computer systems mathematical model modification(Національний технічний університет "Харківський політехнічний інститут", 2020) Semenov, Serhii; Weilin, CaoTesting process for penetration into computer systems mathematical model was developed in the article. The proposed model differs from the known by computer systems specialized information platforms security testing capabilities, which made it possible to estimate the penetration test algorithm execution time falling within a given interval probability. The proposed testing process for penetration into computer systems mathematical model was further developed (modified). Modified model distinctive feature is the Erlang distribution as the main one in the state transition processes mathematical formalization. This made it possible on the one hand to unify the mathematical model and present thetesting process at a higher level of the testing hierarchy, on the other hand to simplify it 1.7 times. A security testing mathematical model was developed in order to estimate the simulation results accuracy, based on the known GERT- networks simplification and modification approach. Testing algorithms execution time value mathematical expectation values are obtained and estimated. Comparative modeling results investigations have shown the study values comparability for all three approaches of security testing process mathematical formalization. This confirmed the hypothesis that it is advisable to use a unified mathematical formalization approach, which was implemented in a penetration testing process modified mathematical model.Документ Development of anomalous computer behavior detection method based on probabilistic automaton(National University of Civil Protection of Ukraine, 2019) Chelak, Viktor; Chelak, E.; Gavrylenko, Svitlana; Semenov, SerhiiThis work proposes anomalous computer system behavior detection method based on probabilistic automaton. Main components of the method are automaton structure generation model and its modification procedure. The distinctive feature of the method is the adaptation of the automaton structure generation procedure for detecting attack scenarios of the same type, by restructuring the automaton upon a match and by recalculating the probability of state changes. Proposed method allows to speed up the detection of anomalous computer behavior, as well as to detect anomalies in computer systems, scenario profiles of which only partially match the instances used to generate automaton structure. The obtained results allow us to conclude that the developed meth-od can be used in heuristic analyzers of anomaly detection systems.