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Generating Representative Traffic for Intrusion Detection System Benchmarking
Halifax, N.S., Canada May 16-May 18
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CNSR.2005.353rd Annual Communication Networks and ...
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H. G?neş Kayacík, Nur Zincir-Heywood, "Generating Representative Traffic for Intrusion Detection System Benchmarking," Communication Networks and Services Research, Annual Conference on, pp. 112-117, 3rd Annual Communication Networks and Services Research Conference (CNSR'05), 2005.
 
 
BibTex
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@article{ 10.1109/CNSR.2005.35,
author = {H. G?neş Kayacík and Nur Zincir-Heywood},
title = {Generating Representative Traffic for Intrusion Detection System Benchmarking},
journal ={Communication Networks and Services Research, Annual Conference on},
volume = {0},
year = {2005},
isbn = {0-7695-2333-1},
pages = {112-117},
doi = {http://doi.ieeecomputersociety.org/10.1109/CNSR.2005.35},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Communication Networks and Services Research, Annual Conference on
TI - Generating Representative Traffic for Intrusion Detection System Benchmarking
SN - 0-7695-2333-1
SP112
EP117
A1 - H. G?neş Kayacík,
A1 - Nur Zincir-Heywood,
PY - 2005
KW - Network Security
KW - Intrusion Detection
KW - Traffic Modeling
KW - Markov Models
KW - Self-Organizing Maps
VL - 0
JA - Communication Networks and Services Research, Annual Conference on
ER -
 
H. G?neş Kayacík, Dalhousie University
Nur Zincir-Heywood, Dalhousie University
In this paper, a modeling and simulation framework is proposed for generating data for training and testing intrusion detection systems. The framework can develop models of web usage from web server logs in a data driven fashion and the actual traffic is generated by employing the web browser installed on the host. Additionally, we employed an intrusion detection system as a traffic analyzer to validate the synthetic data that the framework generated and compared it against the standard intrusion detection system benchmark data, namely KDD 99 datasets.
Index Terms:
Network Security, Intrusion Detection, Traffic Modeling, Markov Models, Self-Organizing Maps
Citation:
H. G?neş Kayacík, Nur Zincir-Heywood, "Generating Representative Traffic for Intrusion Detection System Benchmarking," cnsr, pp.112-117, 3rd Annual Communication Networks and Services Research Conference (CNSR'05), 2005
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