Intrusion Detection Localization Method of Large Association Embedded Network Equipment

DOI

10.2991/iccset-14.2015.64How to use a DOI?

Keywords

intrusion detection; association embedded network; neural network

Abstract

The method of intrusion detection of embedded network equipment in large association is researched. In the process of large-scale embedded network device associated intrusion detection, the intrusion detection results of network equipment directly affect the stability and security of the network. For this, an intrusion detection method of large-scale embedded network device is proposed based on improved ART2. When there are amount of memory models in artificial neural network, effective organization for learning the model can be carried out, and improve the detection efficiency, the judgment condition adjustment is reduced by linear combination of amplitude and phase, the cluster size difference is reduced, thus, the network intrusion detection and positioning of device are completed. The experiment results show that, by using the improved ART2 algorithm for large embedded network device intrusion detection, it can simplify the training set, shorten the detection time, the accuracy of detection is improved.

Copyright

© 2015, 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/).

Download article (PDF)

TY  - CONF
AU  - Liao Lang
AU  - Zhenjia Zhu
PY  - 2015/01
DA  - 2015/01
TI  - Intrusion Detection Localization Method of Large Association Embedded Network Equipment
BT  - Proceedings of the 2014 International Conference on Computer Science and Electronic Technology
PB  - Atlantis Press
SP  - 293
EP  - 296
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccset-14.2015.64
DO  - 10.2991/iccset-14.2015.64
ID  - Lang2015/01
ER  -