Study on Attribute Reduction Method of Network Intrusion Detection System Based on Granular Computing

DOI

10.2991/icetms.2013.394How to use a DOI?

Keywords

granular computing; network intrusion detection system; attribute reduction

Abstract

Based on granular computing theory, according to the problem of intrusion detection classification performance reduced by redundant attribute in high dimensional network data, an attribute reduction method of network intrusion detection system based on granular computing is given, the redundant attribute is removed under the condition of keeping the information integrity of original attribute set to reduce the attribute dimension of data. The example analysis indicates that this method reduces the training and detection time, and improves the computing efficiency of system in order to reduce the data storage, it provides a new idea for processing massive large data.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Tianyi Leng
AU  - Haiyan Li
PY  - 2013/06
DA  - 2013/06
TI  - Study on Attribute Reduction Method of Network Intrusion Detection System Based on Granular Computing
BT  - Proceedings of the 2013 Conference on Education Technology and Management Science (ICETMS 2013)
PB  - Atlantis Press
SP  - 1469
EP  - 1471
SN  - 1951-6851
UR  - https://doi.org/10.2991/icetms.2013.394
DO  - 10.2991/icetms.2013.394
ID  - Leng2013/06
ER  -