Кафедра "Комп'ютерна інженерія та програмування"

Постійне посилання колекціїhttps://repository.kpi.kharkov.ua/handle/KhPI-Press/1095

Офіційний сайт кафедри https://web.kpi.kharkov.ua/cep

Від 26 листопада 2021 року кафедра має назву – "Комп’ютерна інженерія та програмування"; попередні назви – “Обчислювальна техніка та програмування”, “Електронні обчислювальні машини”, первісна назва – кафедра “Математичні та лічильно-вирішальні прилади та пристрої”.

Кафедра “Математичні та лічильно-вирішальні прилади та пристрої” заснована 1 вересня 1961 року. Організатором та її першим завідувачем був професор Віктор Георгійович Васильєв.

Кафедра входить до складу Навчально-наукового інституту комп'ютерних наук та інформаційних технологій Національного технічного університету "Харківський політехнічний інститут". Перший випуск – 24 інженери, підготовлених кафедрою, відбувся в 1964 році. З тих пір кафедрою підготовлено понад 4 тисячі фахівців, зокрема близько 500 для 50 країн світу.

У складі науково-педагогічного колективу кафедри працюють: 11 докторів технічних наук, 21 кандидат технічних наук, 1 – економічних, 1 – фізико-математичних, 1 – педагогічних, 1 доктор філософії; 9 співробітників мають звання професора, 14 – доцента, 2 – старшого наукового співробітника.

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2017 - 201922020 - 20222

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Автор: search.filters.author.Gavrylenko, SvitlanaКлючові слова: search.filters.subject.computer system

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Зараз показуємо 1 - 4 з 4
  • Ескіз
    Документ
    Development of method for identification the computer system state based on the decision tree with multidimensional nodes
    (Запорізький національний технічний університет, 2022) Gavrylenko, Svitlana; Chelak, V. V.; Semenov, S. G.
    Context. The problem of identifying the state of a computer system is considered. The object of the research is the process of computer system state identification. The subject of the research is the methods of constructing solutions for computer system state identification. Objective. The purpose of the work is to develop a method for decision trees learning for computer system state identification. Method. A new method for constructing a decision tree is proposed, combining the classical model for constructing a decision tree and the density-based spatial clustering method (DBSCAN). The simulation results showed that the proposed method makes it possible to reduce the number of branches in the decision tree, which will increase the efficiency of identifying the state of the computer system. Belonging to hyperspheres is used as a criterion for decision-making, which enables to increase the identification accuracy due to the nonlinearity of the partition plane and to perform a more optimal adjustment of the classifier. The method is especially effective in the presence of initial data with high correlation coefficients, since it combines them into one or more multivariate criteria. An assessment of the accuracy and efficiency of the developed method for identifying the state of a computer system is carried out. Results. The developed method is implemented in software and researched in solving the problem of identifying the state of the functioning of a computer system. Conclusions. The carried out experiments have confirmed the efficiency 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 a computer system. Prospects for further research may consist in the development of an ensemble of decision trees.
  • Ескіз
    Документ
    Development and comparative analysis of computer system state identification methods based on ensemble algorithms
    (Інжиніринг, 2020) Gavrylenko, Svitlana; Sheverdin, Illia
    The scientific novelty of the results obtained consists in creating ensemble methods for classifying the state of a computer system without a teacher and with a teacher. The method based on the "Isolation Forest" algorithm can be used as an express method for analyzing a computer system state. This will allow not only to identify the state of a computer system state, but also to highlight the name of the abnormal processes. This method can also be used to generate labeled data and use it as the source data of the ensemble algorithm with a teacher. The algorithm with a teacher built according to the C4.5 algorithm is more accurate and can be used to refine the result of identifying a computer system state using the method based on the "Isolation Forest" algorithm.
  • Ескіз
    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, Viktor
    Methods 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.
  • Ескіз
    Документ
    Investigation of intrusion in computer systems based on the Hurst exponent
    (NTU "KhPI", 2017) Gavrylenko, Svitlana; Chelak, Viktor; Bilogorskiy, Nick
    The 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.