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International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 1
Adaptive Neuro-Fuzzy Intrusion Detection Systems
Las Vegas, Nevada
April 05-April 07
ISBN: 0-7695-2108-8
ASCII Text
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Sampada Chavan, Khusbu Shah, Neha Dave, Sanghamitra Mukherjee, Ajith Abraham, Sugata Sanyal, "Adaptive Neuro-Fuzzy Intrusion Detection Systems," Information Technology: Coding and Computing, International Conference on, vol. 1, pp. 70, International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 1, 2004.
 
 
BibTex
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@article{ 10.1109/ITCC.2004.1286428,
author = {Sampada Chavan and Khusbu Shah and Neha Dave and Sanghamitra Mukherjee and Ajith Abraham and Sugata Sanyal},
title = {Adaptive Neuro-Fuzzy Intrusion Detection Systems},
journal ={Information Technology: Coding and Computing, International Conference on},
volume = {1},
year = {2004},
isbn = {0-7695-2108-8},
pages = {70},
doi = {http://doi.ieeecomputersociety.org/10.1109/ITCC.2004.1286428},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Information Technology: Coding and Computing, International Conference on
TI - Adaptive Neuro-Fuzzy Intrusion Detection Systems
SN - 0-7695-2108-8
SP
EP
A1 - Sampada Chavan,
A1 - Khusbu Shah,
A1 - Neha Dave,
A1 - Sanghamitra Mukherjee,
A1 - Ajith Abraham,
A1 - Sugata Sanyal,
PY - 2004
KW - null
VL - 1
JA - Information Technology: Coding and Computing, International Conference on
ER -
 
Sampada Chavan, SNDT University, India
Khusbu Shah, SNDT University, India
Neha Dave, SNDT University, India
Sanghamitra Mukherjee, SNDT University, India
Ajith Abraham, Oklahoma State University, USA
Sugata Sanyal, Tata Institute of Fundamental Research, India
The Intrusion Detection System architecture commonly used in commercial and research systems have a number of problems that limit their configurability, scalability or efficiency. In this paper, two machine-learning paradigms, Artificial Neural Networks and Fuzzy Inference System, are used to design an Intrusion Detection System. SNORT is used to perform real time traffic analysis and packet logging on IP network during the training phase of the system. Then a signature pattern database is constructed using protocol analysis and Neuro-Fuzzy learning method. Using 1998 DARPA Intrusion Detection Evaluation Data and TCP dump raw data, the experiments are deployed and discussed.
Citation:
Sampada Chavan, Khusbu Shah, Neha Dave, Sanghamitra Mukherjee, Ajith Abraham, Sugata Sanyal, "Adaptive Neuro-Fuzzy Intrusion Detection Systems," itcc, vol. 1, pp.70, International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 1, 2004
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