Neural network classifier of attacks in IP telephony

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86090921" target="_blank" >RIV/61989100:27240/14:86090921 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1117/12.2050671" target="_blank" >http://dx.doi.org/10.1117/12.2050671</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1117/12.2050671" target="_blank" >10.1117/12.2050671</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Neural network classifier of attacks in IP telephony

Popis výsledku v původním jazyce

Various types of monitoring mechanism allow us to detect and monitor behavior of attackers in VoIP networks. Analysis of detected malicious traffic is crucial for further investigation and hardening the network. This analysis is typically based on statistical methods and the article brings a solution based on neural network. The proposed algorithm is used as a classifier of attacks in a distributed monitoring network of independent honeypot probes. Information about attacks on these honeypots is collected on a centralized server and then classified. This classification is based on different mechanisms. One of them is based on the multilayer perceptron neural network. The article describes inner structure of used neural network and also information about implementation of this network. The learning set for this neural network is based on real attack data collected from IP telephony honeypot called Dionaea. We prepare the learning set from real attack data after collecting, cleaning and

Název v anglickém jazyce

Neural network classifier of attacks in IP telephony

Popis výsledku anglicky

Various types of monitoring mechanism allow us to detect and monitor behavior of attackers in VoIP networks. Analysis of detected malicious traffic is crucial for further investigation and hardening the network. This analysis is typically based on statistical methods and the article brings a solution based on neural network. The proposed algorithm is used as a classifier of attacks in a distributed monitoring network of independent honeypot probes. Information about attacks on these honeypots is collected on a centralized server and then classified. This classification is based on different mechanisms. One of them is based on the multilayer perceptron neural network. The article describes inner structure of used neural network and also information about implementation of this network. The learning set for this neural network is based on real attack data collected from IP telephony honeypot called Dionaea. We prepare the learning set from real attack data after collecting, cleaning and

Druh

D - Stať ve sborníku

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of SPIE - The International Society for Optical Engineering. Volume 9118

ISBN

978-1-62841-055-6

ISSN

0277-786X

e-ISSN

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Počet stran výsledku

7

Strana od-do

"A1"-"A7"

Název nakladatele

SPIE

Místo vydání

Bellingham

Místo konání akce

Baltimore

Datum konání akce

7. 5. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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