Literature Database Entry

hoehlein2011signature


Philip Klaus Höhlein, "Signature-based Attack Detection on Flow Data," Pre-Master's Thesis (Studienarbeit), Department of Computer Science, University of Erlangen, May 2011. (Advisors: Tobias Limmer and Falko Dressler)

Abstract

Due to the rising data rates available via so called high-speed Internet connections, the network traffic increased considerably. Unfortunately also the malicious usage of the Internet increased enormously and separately, attack detection mechanisms are essential. Due to the high packet data rates network data inspection becomes much complexer. Therefore it becomes impossible to inspect each network packet and consequently attacks could remain undetected. To get a compact representation of the whole network traffic, network packets can be aggregated into IP Flow Information eXport (IPFIX) flow records In our approach we want to detect attacks by utilizing these aggregated flow records for suspicious signatures. As a reference implementation for creating and processing IPFIX flow records, we will use the open source software Vermont. Our approach tries to detect attacks with help of signature-based rules that are tested on each flow record. Therefore we need to analyze which signatures of a flow record are of interest for intrusion detection and define a syntax for our signature rules. Moreover we will discuss, how to match rules efficiently and approach, present our implementation of a flow signature matcher. It will be developed as a module for Vermont. Moreover we will test the performance of our and compare it with Snort, a state of the art NIDS.

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Philip Klaus Höhlein

BibTeX reference

@phdthesis{hoehlein2011signature,
    author = {H{\"{o}}hlein, Philip Klaus},
    advisor = {Limmer, Tobias and Dressler, Falko},
    title = {{Signature-based Attack Detection on Flow Data}},
    institution = {Department of Computer Science},
    year = {2011},
    month = {May},
    location = {Erlangen, Germany},
    school = {University of Erlangen},
    type = {Pre-Master's Thesis (Studienarbeit)},
   }
   
   

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