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Monitoring Network Trafic of Linux Server
Pospíchal, Petr ; Ščuglík, František (referee) ; Ráb, Jaroslav (advisor)
Today the world is facing a very fast expansion of the Internet. Every day, more and more companies rely on services provided by network connections between computer systems. Enormous growth of data volume being transferred also requires more sophisticated systems. Thus it's more complicated to maintain the whole tree of network systems. Key issue to maintain reliability of services and profit, is to have perfect overview of each entity's availability. In a world where most of important systems are being run on UNIX-type operation systems is good to have a tool which allows easy access to information related to a system. The topic of this Bachelory work is to describe both concept and implementation of such tool.
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Network Traffic Analysis Based on Sketches
Dřevo, Aleš ; Kekely, Lukáš (referee) ; Bartoš, Václav (advisor)
Aim of this thesis is to create a program for network traffic analysis and for detection of anomallies in the traffic. The Heavy-Changes Detection technique which falls within the Data stream algorithm category is used to do so. Special structures called sketches are used for data processing. These structures are capable of maintaining large amounts of data with low memory consumption. Programs from Nemea system for which this project is created are used for gathering necessary network data.
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Web Portal for Network Traffic Reporting
Dufek, Milan ; Straka, Martin (referee) ; Tobola, Jiří (advisor)
This thesis deals with gathering and analysis of statistic data about network traffic, it also deals with preserving and displaying such a data. The goal of this thesis is simple and quick user interface in web portal. The source of the statistic data is NetFlow technology. We use NfDump tool for reading the gathered data. Implementation is done in PHP, XHTML, CSS and JavaScript. SQLite Database is used for preserving the data.
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Prediction of data flow in computer networks
Zvěřina, Lukáš ; Sobek, Jiří (referee) ; Vychodil, Petr (advisor)
The aim of this thesis was to study problems of prediction of data in computer networks. Furthermore, this work deals with network traffic and analyzing its properties. In this study were analyzed the possibilities of network traffic prediction using Farima model, the theory of chaos with Lyapunov exponents and neural networks. Possibilities of prediction with the focus on neural network were discussed in detail here, mainly on recurrent neural networks. Prediction was performed in Matlab development environment in Neural Network Toolbox, where they were created, trained and evaluated neural network to predict specific types of network traffic. For testing were selected Elman network NARX network and general LRN recurrent network. The results were clearly organized into tables and plotted in graphical relationships before and after the use of predictive techniques designed to final evaluation.
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Graphical Visualization of Network Traffic Geographical Data
Kachlík, Jakub ; Holkovič, Martin (referee) ; Hynek, Jiří (advisor)
During ongoing Internet attacks is important to find out as much information about the attacker as possible and to pass this information clearly to the network administrator. The Flowmon monitoring system is currently able to determine the source destination of sent packets, group them into flows and write them into a table. The data visualized in this way are confusing to create a geographical analysis of the attack. The objective of this work is to create a web information dashboard that will display geographic visualizations of network traffic. It will provide more detailed and easier-to-understand analysis to users of the tools.
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Nonlinear analysis and prediction of network traffic
Člupek, Vlastimil ; Burget, Radim (referee) ; Vychodil, Petr (advisor)
This thesis deal with an analysis of network traffic and its properties. In this thesis are discussed possibilities of prediction network traffic by FARIMA model, theory of chaos with Lyapunov exponent and by neural networks. The biggest attention was dedicated to prediction network traffic by neural networks. In Matlab with using Neural Network Toolbox were created, trained and tested recurrent networks for prediction specific types of network traffics, which was captured on local network. There were choosed Elman network, LRN and NARX network to test the prediction of network traffic, results were discussed. Thesis also introduce area of application ability prediction of network traffic, there is introduce design of system for dynamic allocation bandwidth with particular description of its prediction part. Thesis also states possible use designed system for dynamic allocation of bandwidth.
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Graphical Visualization of Network Traffic Geographical Data
Kachlík, Jakub ; Holkovič, Martin (referee) ; Hynek, Jiří (advisor)
During ongoing Internet attacks is important to find out as much information about the attacker as possible and to pass this information clearly to the network administrator. The Flowmon monitoring system is currently able to determine the source destination of sent packets, group them into flows and write them into a table. The data visualized in this way are confusing to create a geographical analysis of the attack. The objective of this work is to create a web information dashboard that will display geographic visualizations of network traffic. It will provide more detailed and easier-to-understand analysis to users of the tools.
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Network Traffic Analysis Based on Sketches
Dřevo, Aleš ; Kekely, Lukáš (referee) ; Bartoš, Václav (advisor)
Aim of this thesis is to create a program for network traffic analysis and for detection of anomallies in the traffic. The Heavy-Changes Detection technique which falls within the Data stream algorithm category is used to do so. Special structures called sketches are used for data processing. These structures are capable of maintaining large amounts of data with low memory consumption. Programs from Nemea system for which this project is created are used for gathering necessary network data.
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Detection of anomalies in data center network traffic
Korzhasbayeva, Leila ; Uher, Václav (referee) ; Burget, Radim (advisor)
Ve velkých společnostech existuje spousta kriticky důležitých strojů pracujících bez přestávky každý den. Jednoduché Log Management řešení není vždy dostatečné k zachycení všech dat, která tečou produkčním prostředí. Ani bezpečnostní analytik není vždy schopen sledovat každý zdroj v prostředí, chytat změny v běžném provozu. Zde je bod, kde nám stroj může pomoci. Detekce anomálií v prostředí je hlavním cílem tohoto projektu. Existuje několik řešení prezentovaných a testovaných na datech ze serverů v reálném prostředí definované společnosti. Některé false positives stále se mohou objevovat, ale je to dobrá příležitost k vyřešení v budoucím výzkumu.
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