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Документ Відкритий доступ 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, IhorThe 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.Документ Відкритий доступ 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, DmytroA 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.