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Документ Assessment of the state of the computer system based on the hurst exponent(Technical University of Sofia, 2017) Semenov, Sergei; Gavrylenko, Svitlana; Chelak, ViktorThe method of identifying abnormal behavior of computer systems based on the Hurst exponent is examined in this report. Results of the research suggest the possibility of using the Hurst exponent for identifying the anomalous behavior of computer systems in the overall system to detect malicious software.Документ Computer system anomalous state detection method based on fuzzy logic(ФОП Петров В. В., 2019) Chelak, Viktor; Gavrylenko, Svitlana; Chelak, E.Документ Developing parametrical criterion for registering abnormal behavior in computer and telecommunication systems on the basis of economic tests(Національна академія управління, 2016) Semenov, Sergei G.; Gavrylenko, Svitlana; Chelak, ViktorIn this article a study of malicious attacks' detection methods of computer and telecommunication systems is conducted. The need to improve the IT models and to substantiate the choice of criteria for assessing the abnormal behavior in computer and telecommunication systems is revealed. The appropriateness of using the jitter of the BDS-test value as an indicator of abnormal behavior in computer and telecommunication systems, and the percentage of deviation in the presented value from the values chosen as a result of the experiment as the grading criteria is grounded.Документ Development of a heuristic antivirus scanner based on the file's pe-structure analysis(Вінницький національний технічний університет, 2017) Gavrylenko, Svitlana; Melnyk, М. S.; Chelak, ViktorMethods for constructing antivirus programs, their advantages and disadvantages are considered. The PE-structure of malicious and secure software is analyzed. The API-functions and strings inherent in these files are found and some of them are selected for further analysis. The selected features are used as inputs for the system of fuzzy inferences. A model of a fuzzy inference system based on the Mamdani fuzzy logic method is developed and tested. The obtained results of the research showed the possibility of using the developed malicious software identification system in heuristic analyzers of intrusion detection systems.Документ Development of a heuristic scanner for an antivirus program on the basis of the mamdani fuzzy logic method(Technical University of Sofia, 2018) Gavrylenko, Svitlana; Chelak, Viktor; Gornostal, AlekseyThe article considers the means of antivirus protection of information, their advantages and disadvantages. An analysis of modern decision-making systems is carried out. The system of fuzzy logic is chosen. A module based on the Mamdani fuzzy logic method was developed, and the developed system was tested. The obtained results of the research showed the possibility of using the developed module in heuristic analyzers of intrusion detection systems.Документ Development of a method for identifying the state of a computer systemusing fuzzy cluster analysis(Національний технічний університет "Харківський політехнічний інститут", 2020) Gavrylenko, Svitlana; Chelak, Viktor; Hornostal, Oleksii; Vassilev, VelizarThe subject of this article is the study of methods for identifying the state of computer systems. The purpose of the article is to develop a method for identifying the abnormal state of a computer system based on fuzzy cluster analysis. Objective: to analyze methods for identifying the state of computer systems; to conduct research on the selection of source data; to develop a method for identifying the state of a computer system with a small sample or fuzzy source data; to investigate and justify the procedure for comparing fuzzy distances between grouping centers and clustering objects; to develop a software and test. The methodsused in the paper: cluster analysis, fuzzy logic tools. The following resultswere obtained: a method was theoretically substantiated and investigated for identifying the state of a computer system with a small sample or fuzziness of the initial data, which is distinguished by the use of the method based on fuzzy cluster analysis by the refined grouping procedure. To solve the clustering problem, we used a special procedure for comparing fuzzy distances between grouping centers and clustering objects. Software was developed and testing of the developed method was performed. The quality of classification based on the ROC analysis is assessed. Conclusions. The scientific novelty of the results is as follows: a study was conducted on the selection of source data for analysis; a method for identifying the state of a computer system based on fuzzy cluster analysis using a special procedure for comparing fuzzy distances between grouping centers and clustering objects has been developed. This allowed to improve the classification quality to 22 %.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.Документ Development of Computer State Identification Method Based on Boosting Ensemble(2021) Chelak, Viktor; Gavrylenko, SvitlanaThis work is about developing a modification of boosting method by using a special preprocessing procedure to improve the accuracy of computer system state identification. The aim of the research is to develop method for detection computer threats, malware, etc. Experimental research have confirmed the effectiveness of the proposed method, which makes it possible to recommend it for practical use in order to improve the accuracy of identifying the state of the computer system. Prospects for further research may be to develop an ensemble of fuzzy decision trees based on the proposed method, optimizing their software implementation.Документ Intrusion detection in computer systems(Technical University of Sofia, 2016) Gavrylenko, Svitlana; Chelak, Viktor; Hornostal, AlekseyThe work proposes to use the mathematical formalism of statistical analysis based on the BDS-test, Shewhart control cards and CUSUM to develop patterns of identification of the computer system in a state of computer viruses attacks.Документ Investigation of intrusion in computer systems based on the Hurst exponent(NTU "KhPI", 2017) Gavrylenko, Svitlana; Chelak, Viktor; Bilogorskiy, NickThe subjectof the research in this article is the analysis of intrusion detection methods in computer systems.The purpose of the article is to develop effective methods and technologies for countering computer viruses. Tasks: research of modern means of antivirus protection of computer systems; a study of the Hurst index for assessing the state of the computer system; development of a software model for assessing the state of a computer system based on the Hurst index, analysis of the experimental data. The methods usedare: self-similarity assessment of the process based on the Hurst index. The following results are obtained. A method for identified abnormal behavior of a computer system based on the Hurst index is proposed. It is based on the analysis of CPU and RAM. The results of the research showed that theinfluence of a number of viruses on the computer system leads to the aspiration of the Hurstindex to an average value of 0.5, which indicates the randomness of the process. Conclusions. Experimental studies confirm the possibility of using the Hurst index as an integral part of the intrusion detection system in computer systems.Документ Mental health support application based on aritificial intelligence(Національний технічний університет "Харківський політехнічний інститут", 2024) Yelovets, Oleksandr; Arzubov, Mykola; Chelak, Viktor; Pidbutska, Nina; Panfilov, YuryThe current state of human mental health is considered and its content is defined. It describes a program that you install on your gadget to stabilize your mental health. A review and comparison of existing analogues of the mental state support application was carried out, a description of the system and algorithms used to create the mental state support application: speech recognition, dynamic time transformation, artificial neural networks, hidden Markov models, the final speech recognition algorithm. Analysis of affordability is also important, because it affects the possibility of using applications by a wide range of users. a description of the system and algorithms used to create an application for mental state support is presented. The proposed technologies are intertwined with a deep understanding of the human psyche in the context of creating an application for mental stabilization. For further development, you can improve the quality of the theory presented in the application, the speed and efficiency of artificial intelligence, and also constantly add new functions to the application.Документ Method of computer system state identification based on boosting ensemble with special preprocessing procedure(Національний технічний університет "Харківський політехнічний інститут", 2022) Chelak, Viktor; Gavrylenko, SvitlanaThe subject of the research is methods of identifying the state of the Computer System. The object of research is the process of identifying the state of a computer system for information protection. The aim of the research is to develop the method for identifying the state of a computer system for information protection. This article is devoted to the development of method (boosting ensemble) to increase the accuracy of detecting anomalies in computer systems. Methods used: artificial intelligence methods, machine learning, decision tree methods, ensemble methods. The results were obtained: a method of computer system identification based on boosting ensemble with special preprocessing procedure is developed. The effectiveness of using machine learning technology to identify the state of a computer system has been studied. Experimental researches have confirmed the effectiveness of the proposed method, which makes it possible to recommend it for practical use in order to improve the accuracy of identifying the state of the computer system. Conclusions. According to the results of the research, ensemble classifier of computer system state identification based on boosting was proposed. It was found that the use of the proposed classifier makes it possible to reduce the variance to 10%. In addition, due to the optimization of the initial data, the efficiency of identifying the state of the computer was increased. Prospects for further research may be to develop an ensemble of fuzzy decision trees based on the proposed method, optimizing their software implementation.Документ Method of Identifying the State of Computer System under the Condition of Fuzzy Source Data(2020) Gavrylenko, Svitlana; Chelak, Viktor; Kazarinov, MichaelThe purpose of this work is developing a method for identifying the abnormal state of a computer system based on the Bayes' Fuzzy classifier. It allowed us to create a Fuzzy expert identification system with an unlimited number of controlled indicators that belong to a finite interval. Estimation of informativeness of such indicators does not depend on the type of indicator’s functions and on the rule of their usage in the calculated formula. Introduced criterion allowed to estimate indices of the functioning of computer systems presented indistinctly. The quality of classification was evaluated based on ROC analysis. It was found that the method based on Bayes' Fuzzy expert system is qualitative, and its classification speed is almost independent of quantity indicators. Comparative evaluation of Bayes' Fuzzy classifier with Fuzzy clustering classifier and Fuzzy discriminant classifier are performed. In order to regulate the level of false-positive and false-negative classification, recommendations have been developed to manage the level of sensitivity and specificity of a Fuzzy expert system based on the Bayes classifier.Документ Methodological approach to predicting producer prices for petroleum products(Чернігівський національний технологічний університет, 2018) Posokhov, Igor Mikhailovich; Horenko, Nadezhda Oleksiivna; Chelak, ViktorUrgency of the research. Every day, scientists solve problems in economics. To find, which action leads to the expected result with the smallest losses and risks, it’s necessary to predict the further development of events. Target setting. The most widespread problem is the allocation of resources. To make proper calculations and right decisions of distribution, the science of economic theory exists. Actual scientific researches and issues analysis. The studies of Khaikin S. and Callan R. are the most famous among the studies of foreign authors. Yakhyaeva G. E. investigated the theory of neural networks. Matviychuk A. V. suggested a methodical approach to forecasting financial time series with the use of neural networks. Uninvestigated parts of general matters defining. At the moment about 200 methods of estimation are being used, but in practice only a few of them are used. The research objective. The study of each criterion takes a lot of time on preparation of data for the study and careful verification of the original data. For this, it is necessary to choose the correct methodology for developing a forecast to identify the problems to be solved. The statement of basic materials. In this article, the stages of research and prediction are considered of wholesale prices for petroleum products, a methodological approach is proposed in order to evaluate the accuracy of forecasting using neural networks, based on an algorithm with linear partial descriptions of the method of group accounting of the argument. Conclusions. The proposed methodological approach to estimating the accuracy of forecasting using neural networks shows that neural networks allow us to obtain reliable predictions. However, the data on which the training took place had a high degree of similarity among itself, therefore the proposed methodological approach on the one hand does not pretend to be "universal" in forecasting for different sectors of the Ukrainian economy, since different industries have their own characteristics. On the other hand, it can become universal and will allow us to obtain reliable forecasts when taking into account modern features of the development of the Ukrainian economy.Документ Neural networks as decision-making apparatus in antivirus systems(Черкаський державний технологічний університет, 2018) Chelak, Viktor; Chelak, E.; Gavrylenko, SvitlanaДокумент Processing information on the state of a computer system using probabilistic automata(Institute of Electrical and Electronics Engineers, 2017) Semyonov, S. G.; Gavrylenko, Svitlana; Chelak, ViktorThe paper deals with the processing of information about the state of a computer system using a probabilistic automaton. A model of an intelligent system for detection and classification of malicious software is proposed, which compares a set of features that are characteristic for different classes of viruses with multiple states of the machine. The analysis process is reduced to modeling the operation of the automaton taking into account the probability of transition from state to state, which at each step is recalculated depending on the reaction of the environment. The received results of research allow to reach a conclusion about the possibility of using the offered system for detection of the harmful software.