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Sa Li, "Network Data Mining: Untersuchung und Anwendung von Data-Mining-Methoden zur Verkehrsanalyse," Bachelor Thesis, Wilhelm-Schickard-Institute for Computer Science, University of Tübingen, February 2006. (Advisors: Gerhard Münz, Ali Fessi and Falko Dressler)


Im Internet entstehen heute riesige Datenmenge. Data Mining ermöglicht das automatische Auswerten solcher Datenbestände. Es hilft dabei, neue Erkenntnisse aus großen Datenmenge zu erhalten. Anomalie-Erkennung ist eine Methode für Intrusion- Detection Systeme (IDS). Sie beschreibt das normale Verhalten eines Computersystems und Benutzers zum Aufspüren von anormalen, unberechtigten oder schadhaften Aktivitäten in einem Computersystem. Diese Arbeit stellt verschiedene Data-Mining-Methoden (Assoziationsregeln, Klassifikation, Ausreisseranalyse) dar, um auf Basis von NetFlow- Daten Regeln und Mustern für normales Verhalten eines Computersystems zu bilden.

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Sa Li

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    author = {Li, Sa},
    title = {{Network Data Mining: Untersuchung und Anwendung von Data-Mining-Methoden zur Verkehrsanalyse}},
    advisor = {M{\"{u}}nz, Gerhard and Fessi, Ali and Dressler, Falko},
    institution = {Wilhelm-Schickard-Institute for Computer Science},
    location = {T{\"{u}}bingen, Germany},
    month = {2},
    school = {University of T{\"{u}}bingen},
    type = {Bachelor Thesis},
    year = {2006},

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