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System for network device detection and recognition of used protocols
Sasák, Libor ; Fujdiak, Radek (referee) ; Holasová, Eva (advisor)
This master's thesis deals with the recognition of used protocols in a network using machine learning and the creation of a system for this purpose. It focuses on the most widely used industrial and common application protocols and describes selected well-proven machine learning techniques for their recognition. However, priority is given to artificial neural networks. It briefly describes databases and the specific implementation SQLite3 used in the final system implementation. A virtual environment for simulating selected Modbus/TCP, DNP3, HTTPS and FTP protocols is also created and described. Part of the thesis is devoted to the collection, analysis and processing of the data needed to recognize the protocols. Furthermore, it covers the creation and testing of machine learning models for the given protocols. Last but not least, the thesis is devoted to the design of the recognition system and its implementation with a graphical user interface. It also includes testing and evaluation of its advantages and limitations.
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An Integration of SIP Voice Calls into an IRC Client or Gateway
Kocman, David ; Očenášek, Pavel (referee) ; Rychlý, Marek (advisor)
Tato práce popisuje návrh, implementaci a testování Session Initiation Protocol uživatelského agenta, který používá Internet Relay Chat klienta či bránu jako jeho grafické rozhraní. Pro implementaci volání je použita open-source knihovna třetí strany, nazývána liblinphone, a samotný program je napsán v jazyce C/C++. Program je schopen jak volání, tak i zákládních SIP vlastností, jako je registrace u ústředny, překlad čísel na adresy pomocí ENUM a přímé zprávy. Také je k dispozici adresář pro ukládání kontaktů a identit, napsán pomocí knihovny SQLite3 pro C/C++. Výsledek této práce zavádí možnost volání z IRC.
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System for network device detection and recognition of used protocols
Sasák, Libor ; Fujdiak, Radek (referee) ; Holasová, Eva (advisor)
This master's thesis deals with the recognition of used protocols in a network using machine learning and the creation of a system for this purpose. It focuses on the most widely used industrial and common application protocols and describes selected well-proven machine learning techniques for their recognition. However, priority is given to artificial neural networks. It briefly describes databases and the specific implementation SQLite3 used in the final system implementation. A virtual environment for simulating selected Modbus/TCP, DNP3, HTTPS and FTP protocols is also created and described. Part of the thesis is devoted to the collection, analysis and processing of the data needed to recognize the protocols. Furthermore, it covers the creation and testing of machine learning models for the given protocols. Last but not least, the thesis is devoted to the design of the recognition system and its implementation with a graphical user interface. It also includes testing and evaluation of its advantages and limitations.
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