Simulation on the Effective Detection Model for Network Differentiation Intrusion

DOI

10.2991/amcce-15.2015.182How to use a DOI?

Keywords

network intrusion; differentiation; signature database

Abstract

The problem of network differentiation intrusion is researched. Network intrusion has the characteristics of complex changes such as concealed, randomness, difference and abruptness. Traditional method cannot describe the change rules, leading to low correct rate of detection. For this, a detection method for network differentiation intrusion based on artificial immune algorithm is proposed. The dynamic change equation of network differentiation intrusion characteristics is established, to obtain the cross point distribution condition of network differentiation intrusion characteristics. The network differentiation intrusion signature database is updated, and the network differentiation intrusion feature in the database is selected. The results show that the artificial immune algorithm solves the problem existing in traditional algorithm, improves the correct rate of network differentiation intrusion detection.

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/).

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TY  - CONF
AU  - Chun Liu
PY  - 2015/04
DA  - 2015/04
TI  - Simulation on the Effective Detection Model for Network Differentiation Intrusion
BT  - Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering
PB  - Atlantis Press
SP  - 765
EP  - 769
SN  - 1951-6851
UR  - https://doi.org/10.2991/amcce-15.2015.182
DO  - 10.2991/amcce-15.2015.182
ID  - Liu2015/04
ER  -