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Matthias Segschneider, "Entwicklung eines Flow basierten Detektors von Peer-to-Peer Verkehr," Bachelor Thesis, Department of Computer Science, Friedrich–Alexander University of Erlangen–Nuremberg (FAU), September 2008. (Advisors: Tobias Limmer and Falko Dressler)


With the number of internet users and services rising worldwide, also number, rate and quality of attacks continue to increase. Attacks by modern, decentralized organized botnets are rising. This new kind of botnets is based on peer-to-peer technology used by popular file sharing networks like eDonkey or BitTorrent. To hide from traditional detection methods like deep packet inspection they use payload encryption and random port numbers. Subject of this work is the development of a flow-based peer-to-peer detector that is not depending on payload or port number analysis. Therefore I aggregated flow-data of various peer-to-peer networks to bidirectional flows and analysed the communication on the basis of these biflows. My intention was to define and combine suitable detection criteria like the number of simultaneous connections or the portion of failed connection attempts to identify peer-to-peer clients. My experiments and comparisons with the intrusion detection system Snort showed that it is possible to detect almost all peer-to-peer clients identified by Snort and even further more using the nine detection criterias defined by me. On the other hand there is the problem of detecting false positives that is complicated by traffic obfuscation and therefore requires additional examination.

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Matthias Segschneider

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    author = {Segschneider, Matthias},
    title = {{Entwicklung eines Flow basierten Detektors von Peer-to-Peer Verkehr}},
    advisor = {Limmer, Tobias and Dressler, Falko},
    institution = {Department of Computer Science},
    location = {Erlangen, Germany},
    month = {9},
    school = {Friedrich--Alexander University of Erlangen--Nuremberg (FAU)},
    type = {Bachelor Thesis},
    year = {2008},

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