Research of Detection Method of Server Network Storm Attack

DOI

10.2991/iccset-14.2015.11How to use a DOI?

Keywords

intrusion detection; density clustering; feature selection

Abstract

In the detection process of server network storm attack, the traditional method takes the signal detection algorithm, because the attack number is large, the detection error is big. According to the problem, an improved server network storm attack detection method is proposed based on improved density clustering algorithm, the server network storm attack detection problem is transformed into a multi class classification problem, wrapper features selection model is taken, IDBC network connection record distance calculation method is combined, based on DBSCAN clustering results, the data clustering and attack detection is obtained. Simulation results show that, the improved density clustering algorithm is applied in detection of server network storm attack, it can reduce the detection error, the performance of the detection system 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
PY  - 2015/01
DA  - 2015/01
TI  - Research of Detection Method of Server Network Storm Attack
BT  - Proceedings of the 2014 International Conference on Computer Science and Electronic Technology
PB  - Atlantis Press
SP  - 48
EP  - 51
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccset-14.2015.11
DO  - 10.2991/iccset-14.2015.11
ID  - Lang2015/01
ER  -