Перегляд за Автор "Lande, Dmytro"

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    Aggregation of information from diverse networks as the basis for training cyber security specialists on processing ultra large data sets
    (Institute of Special Communication and Information Protection of National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, 2021) Lande, Dmytro; Puchkov, Oleksandr; Subach, Ihor
    The basic principles of training cybersecurity specialists on processing large data sets to solve complex unstructured tasks in the course of their functional responsibilities based on the achievements of Data Science in the field of cybersecurity, by acquiring the necessary competencies and practical application of the latest information technologies based on methods of aggregation of large amounts of data are substantiatedand presented. The most common latest technologiesand tools in the field of cybersecurity, the list of which allows getting a fairly holistic view of what is used today by specialists in the field of Data Science, are considered. The tools you need to have to solve complex problems using big data are analyzed.The subject of the study is the fundamental provisions of the concept of “big data”; appropriate data models; architectural concepts of creating information systems for “big data”; big data analytics, as well as the practical application of big dataprocessing results. The theoretical basis of the training, which includes two sections: “Big Data: theoretical principles”, and “Technological applications for big data”, which, in turn, are logically divided into ten, is considered. As a material and technical basis for the acquisition of practical skills by students, a model based on the system “CyberAggregator” was created and described, which operates and is constantly improved in accordance with the expansion of the list of tasks assigned to it. The CyberAggregator system consists of three main parts: a server for collecting and primary processing of information; an information retrieval server (search engine); an interface server from which the service is provided to users and other systems via the API. The system is based on technological components such as the Elasticsearch information retrieval system, the Kibana utility, the Neo4j database graph management system, JavaScript-based results visualization tools (D3.js) and network information scanningmodules. The system provides the implementation of such functions as the formation of databases from certain information resources; maintaining full-text databases of information; detection of duplicates similar in content to information messages; full-text search; analysis of text messages, determination of tonality, formation of analytical reports; integration with the geographic information system; data analysis and visualization; research of thematic information flows dynamics; forecasting events basedon the analysis of the publications dynamics, etc. The suggested approach allows students to acquire the necessary competencies needed to process effectively large amounts of data from social networks, create systems for monitoring network information on cybersecurity, selection of relevant information from social networks, search engine implementation, analytical research, forecasting.
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    Cybersecurity in AI-Driven Casual Network Formation
    (Igor Sikorsky Kyiv Polytechnic Institute, 2023) Lande, Dmytro; Feher, Anatolii; Strashnoy, Leonard
    The paper describes a methodology for forming thematic causal networks using artificial intelligence and automating the processes of their visualization. The presented methodology is considered on the example of ChatGPT, as an artificial intelligence for analyzing the space of texts and building concepts of causal relationships, and their further visualization is demonstrated on the example of Gephi and CSV2Graph programs. The effectiveness of the disaggregated method in relation to traditional methods for solving such problems is shown by integrating the means of intelligent text analytics and graphical network analysis on the example of the problem of data leakage in information systems and a selection of news clippings on the selected cybersecurity topic.
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    GPT Semantic Networking: A Dream of the Semantic Web – The Time is Now
    (Engineering Ltd, 2023) Lande, Dmytro; Strashnoy, Leonard
    The book presents research and practical implementations related to natural language processing (NLP) technologies based on the concept of artificial intelligence, generative AI, and the concept of Complex Networks aimed at creating Semantic Networks. The main principles of NLP, training models on large volumes of text data, new universal and multi-purpose language processing systems are presented. It is shown how the combination of NLP and Semantic Networks technologies opens up new horizons for text analysis, context understanding, the formation of domain models, causal networks, etc. This book presents methods for creating Semantic Networks based on prompt engineering. Practices are presented that will help build semantic networks capable of solving complex problems and making revolutionary changes in the analytical activity. The publication is intended for those who are going to use large language models for the construction and analysis of semantic networks in order to solve applied problems, in particular, in the field of decision making.
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    OSINT investigation to detect and prevent cyber attacks and cyber security incidents
    (Institute of Special Communication and Information Protection of National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, 2021) Puchkov, Oleksandr; Lande, Dmytro; Subach, Ihor; Boliukh, Mykhailo; Nahornyi, Dmytro
    A methodology for investigatingand predicting cyber incidents based on the use of open sources of information and freely available open source software is offeredand substantiated. The suggestedmethodology refers to suchtypes of methodologies as Open Source Intelligence (OSINT). In addition, it is based on technologies of monitoring the modern Internet space, the concept of processing large amounts of data (Big Data), complex networks (Complex Networks), and extracting knowledge from text arrays (Text Mining). The components of the keyword detection technology (NLTK, Natural Language Toolkit), concepts (SpaCy, NLP), graph visualization and analysis systems are considered in detail. The main idea of analyzing large amounts of data on cybersecurity from the Internet space is to use methods and tools for collecting data using global search engines, aggregating information flows and mining the data obtained. The technique is based on the implementation of such functions as the collection of relevant information from certain information resources using the capabilities of global search engines; automatic scanning and primary processing of information from websites; formation of full-text arrays of information; analysis of text messages, determination of sentiment, formation of analytical reports; integration with a geographic information system; analysis and visualization of information reports; research of dynamics of thematic information flows; forecasting the development of events based on the analysis of the dynamics of publications in the Internet space. In the analytical mode, a number of tools are implemented for graphical presentation of data dynamics, displayed as a time series of the number of messages per day matching to a specific cyber incident,viewing plots from messages on the topic of cyber incidents, clusters grouped by the cluster analysis algorithm. Within the framework of the methodology, it is provided for the formation and inclusion of networks in operational reports from concepts matching to people, organizations, information sources, allowing to explorethe relationship between them.
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    Reference functions of cyber incidents displaying in the media space
    (Igor Sikorsky Kyiv Polytechnic Institute, 2021) Lande, Dmytro; Novikov, Oleksii; Stopochkina, Iryna
    The principles of cyber attacks detection that based on media content are described. Proposed methods are suitable for description of the general trends in the dynamics of information flows concerning cyber incidents. A generalized diagram of cyber attacks stages displaying in the media space is proposed. On the basis of the diagram the basic wavelet functions are selected, which can be considered as a reference for detecting cyber incidents. The proposed wavelets are low-order derivatives of Gaussian function (Wave, «Mexican Hat» and Morlaix wavelets). Retrospective analysis of already implemented information operations is a reliable way to verify them. The problem of forecasting is partly solved by probabilistic estimates in accordance with the type of reference functions.
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    The analysis of cybersecurity subject area terms based on the information diffusion model
    (Igor Sikorsky Kyiv Polytechnic Institute, 2022) Lande, Dmytro; Novikov, Olexiy; Manko, Dmytro
    This research describes a comparison of the information diffusion model, built on the basis of cellular automata with the real statistics the dynamics of the use of terms from the field of cybersecurity in the information flows of the Internet. The information diffusion model is used with different parameters of the intensity of the information propagation. The cross-correlation of dynamics of the dissemination of new information in the model with the dynamics of the occurrence of concepts of the real subject area has been calculated. A high correlation dynamic of the terms occurrence with the dynamics given by the model at the selected parameters is shown. The research results allow fixing the model parameters that can further perform forecasting. The advantage of the information diffusion model based on cellular automata is the simplicity and clarity of a small number of parameters, and the ability to change them in accordance with the data on the actual occurrence of special terminology in information flows. The dynamics of the information diffusion model under various parameters allows us to determine centroids for the subsequent clustering of domain terms.
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    Корпоративная система мониторинга сетевых информационных ресурсов на основе мультиагентного подхода
    (Institute of special communication and information security of National technical university of Ukraine «Kyiv polytechnic institute», 2016) Ландэ, Дмитрий; Додонов, Вадим; Коваленко, Тарас; Lande, Dmytro; Dodonov, Vadym; Kovalenko, Taras
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    Методика розроблення сценаріїв розвитку ситуації на основі аналізу інформаційного простору
    (Institute of Special Communication and Information Protection of National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, 2017) Ланде, Дмитро Володимирович; Бойченко, Андрій Васильович; Lande, Dmytro; Boichenko, Andrii
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    Нелинейные свойства мультиагентной модели распространения новостей
    (Institute of special communication and information security of National technical university of Ukraine «Kyiv polytechnic institute», 2016) Ландэ, Дмитрий; Додонов, Вадим; Lande, Dmytro; Dodonov, Vadym
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    Особливості побудови систем розподіленого контентмоніторингу глобальних інформаційних мереж
    (Institute of Special Communication and Information Protection of National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, 2017) Ланде, Дмитро Володимирович; Кондратенко, Ярослав Анатолійович; Lande, Dmytro; Kondratenko, Yaroslav
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    Порівняльна оцінка критеріїв центральності в ієрархічних мережах
    (Institute of special communication and information security of National technical university of Ukraine «Kyiv polytechnic institute», 2015) Ланде, Дмитро Володимирович; Сулема, Ольга Костянтинівна; Lande, Dmytro; Sulema, Olga