Comparison of artificial intelligence classifiers for SIP attack data

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F63839172%3A_____%2F16%3A10130740" target="_blank" >RIV/63839172:_____/16:10130740 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1117/12.2225292" target="_blank" >http://dx.doi.org/10.1117/12.2225292</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1117/12.2225292" target="_blank" >10.1117/12.2225292</a>

Result language
angličtina
Original language name
Comparison of artificial intelligence classifiers for SIP attack data
Original language description
Honeypot application is a source of valuable data about attacks on the network. We run several SIP honeypots in various computer networks, which are separated geographically and logically. Each honeypot runs on public IP address and uses standard SIP PBX ports. All information gathered via honeypot is periodically sent to the centralized server. This server classifies all attack data by neural network algorithm. The paper describes optimizations of a neural network classifier, which lower the classification error. The article contains the comparison of two neural network algorithm used for the classification of validation data. The first is the original implementation of the neural network described in recent work; the second neural network uses further optimizations like input normalization or cross-entropy cost function. We also use other implementations of neural networks and machine learning classification algorithms. The comparison test their capabilities on validation data to find the optimal classifier. The article result shows promise for further development of an accurate SIP attack classification engine.
Czech name
—
Czech description
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Project
<a href="/en/project/LM2010005" target="_blank" >LM2010005: Large Infrastructure CESNET</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Machine Intelligence and Bio-inspired Computation: Theory and Applications X
ISBN
978-1-5106-0091-1
ISSN
1996-756X
e-ISSN
—
Number of pages
6
Pages from-to
—
Publisher name
SPIE
Place of publication
Bellingham, Washington, US
Event location
Baltimore, Maryland, US
Event date
Apr 17, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000389681700003

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