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Network Traffic Visualization
Matoušek, Martin ; Bartoš, Václav (referee) ; Kováčik, Michal (advisor)
Bachelor thesis deals with visualization of network traffic by NetFlow data. In the theoretical part describes NetFlow technology thet is used for monitoring of computer network . Then I introduce theory of graph layouts . Purpose of the thesis is to crate tool for visualization data.
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Packet Filtering in Computer Networks
Holuša, Jan ; Kováčik, Michal (referee) ; Kajan, Michal (advisor)
This bachelor's thesis deals with packet classification in computer networks. It describes algorithms which are implemented in experimental Netbench framework. For some of them, there are examples of data structures and searching methods. Part of this thesis is implementation of modular packet classification algorithm. Another part of this thesis describes experiments with this algorithm to find its suitable parameters and experiments with Netbench algorithms for comparison of their space and computational complexity.
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Malicious Domains Detection Using Analysis of DNS Traffic
Podešvová, Vlasta ; Bartoš, Václav (referee) ; Kováčik, Michal (advisor)
The aim of this bachelor's thesis is to design, implement and test a system for malicious domain detection in data sets obtained from real network traffic. It is aimed specifically on detection of DGA botnet activities. This detection is provided by analysis of domain name syntax. Part of the solution is focused at building a model from a set of legal domain names. This model is used for domain name syntax analysis and user of the final system is allowed to choose his own model data. Overall this thesis brings a view on the efficiency of implemented methods of malicious domain detection.
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HTTP Application Performance Monitoring
Knapik, Martin ; Kováčik, Michal (referee) ; Bartoš, Václav (advisor)
Goal of this bachelor thesis was to create solution for monitoring and analysis of network performance of HTTP server using Nemea framework and NetFlow data. For this purpose, I've created Nemea module for filtering, parsing and saving NetFlow data enhanced by informations gained from HTTP plugin on exporter. For analysis and user interface, webpage based on Django framework was created, used for displaying statistics that are useful for users in order to reveal problems with monitored servers. Result of my work is product, which is demonstrating possibility of using of Nemea system for passive monitoring of HTTP servers.
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Generating of DNS Service Attacks
Tutko, Jakub ; Bartoš, Václav (referee) ; Kováčik, Michal (advisor)
Availability and security are the most important requirements for Internet services. It is therefore necessary to detect the network anomalies, which have the greatest impact on these requirements. Therefore the great emphasis must be placed on development of detection mechanisms that keep pace with increasingly sophisticated network anomalies. The aim of this work is to analyze and replicate the most common DNS service attacks. Collected data from these attack generators can be used for better understanding of their behavior, what leads to improved and more effective detection mechanisms.
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Malicious Domains Detection Using Analysis of DNS Traffic
Ambrušová, Eva ; Žádník, Martin (referee) ; Kováčik, Michal (advisor)
The aim of this thesis is the detection of malicious domains based on passive analysis of DNS traffic. It represents the design and implementation of a system which proceeds DNS anomaly detection based on a structure of the domain name by using the entropy and a frequency characteristics of n-grams. The system was tested on DNS data obtained from the real traffic and the functionality of implemented detectors was verified by testing and analysis of results.
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Automated Development of Network Attack Detectors
Huták, Lukáš ; Kováčik, Michal (referee) ; Žádník, Martin (advisor)
The thesis is focused on automated development of network attack detectors. It describes a design of patterns developed for normal and offensive behaviors based on monitoring network traffic of selected services. Patterns are represented by statistics with a focus on suitable metrics. Using machine learning algorithms attack detectors are created from behavioral patterns. Finally, a module was implemented for Nemea system in C/C++ programming language based on the proposal.
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Analysis of Captured DNS Traffic
Hmeľár, Jozef ; Kekely, Lukáš (referee) ; Kováčik, Michal (advisor)
This thesis is focused on the analysis of captured DNS traffic. Introduction of this thesis is focused of basic desciption of computer networks , DNS and description of network flows. Then, the work focused on analysis Netflow format, IPFIX and PCAP, the analysis and implementation of tool for analyzing DNS traffic in C++ programming language. The conclusion is devoted to the results of the implemented tools.
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Effective Network Anomaly Detection Using DNS Data
Fomiczew, Jiří ; Žádník, Martin (referee) ; Kováčik, Michal (advisor)
This thesis describes the design and implementation of system for effective detection of network anomaly using DNS data. Effective detection is accomplished by combination and cooperation of detectors and detection techniques. Flow data in NetFlow and IPFIX formats are used as input for detection. Also packets in pcap format can be used. Main focus is put on detection of DNS tunneling. Thesis also describes Domain Name System (DNS) and anomalies associated with DNS.
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