Nowadays, the traffic tomography represents an integral component in converged networks and systems for detecting their behavioral characteristics. The dissertation deals with research of its implementation with the use of evolutionary algorithms. The research was mainly focused on innovation and solving behavioral detection data flows in networks and network anomalies using tomography and evolutionary algorithms. Within the dissertation has been proposed a new algorithm, emerging from the basics of the statistical method survival analysis, combined with a genetics’ algorithm. The proposed algorithm was tested in a model of a self-created network probe using the Python programming language and Cisco laboratory network devices. Performed tests have shown the basic functionality of the proposed solution.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:320776 |
| Date | January 2017 |
| Creators | Oujezský, Václav |
| Contributors | Sýkora, Jiří, Polívka, Michal, Škorpil, Vladislav |
| Publisher | Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií |
| Source Sets | Czech ETDs |
| Language | Czech |
| Detected Language | English |
| Type | info:eu-repo/semantics/doctoralThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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