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Visualization of Longest Prefix Match Algorithms
Fomiczew, Jiří ; Matoušek, Jiří (referee) ; Kováčik, Michal (advisor)
This thesis describes the design and implementation of program for vizualization of algorithms for longest pre fix match (LPM), which is one of the most important tasks for packet classi cation and routing in TCP/IP networks. It describes necessary theory and details about selected algorithms - Trie, Tree Bitmap and CPE. Furthermore, it describes the design and implementation of program for vizualization of the search process of these algorithms with emphasis on the potential use for educational purposes. Finally, it describes the possibilities for future development and expansion of the program.
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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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Visualization of Longest Prefix Match Algorithms
Fomiczew, Jiří ; Matoušek, Jiří (referee) ; Kováčik, Michal (advisor)
This thesis describes the design and implementation of program for vizualization of algorithms for longest pre fix match (LPM), which is one of the most important tasks for packet classi cation and routing in TCP/IP networks. It describes necessary theory and details about selected algorithms - Trie, Tree Bitmap and CPE. Furthermore, it describes the design and implementation of program for vizualization of the search process of these algorithms with emphasis on the potential use for educational purposes. Finally, it describes the possibilities for future development and expansion of the program.
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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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