Network intrusion detection model based on genetic ant colony algorithm
- DOI
- 10.2991/amcce-15.2015.203How to use a DOI?
- Keywords
- intrusion characteristics; genetic algorithm; ant colony algorithm; pheromone concentration
- Abstract
The traditional network intrusion detection is performed on single-dimensional data feature of invasion, once the intrusion has intrusion feature of abnormally high-dimensional data, which can not achieve a unified detection rules, resulting in decreasing efficiency and accuracy of detection. This paper proposes a network intrusion detection method based on genetic ant colony optimization algorithm. According to genetic algorithm building individual coding, employing fitness function to initialize the population, setting pheromone of ants and establishing global pheromone updating rules by ant colony state transition rules, and then ultimately intrusion detection network is accomplished. Experimental results show that modified algorithm for network intrusion detection can improve the speed of training and testing, with significant advantages on increasing detection rate and reducing fault rate.
- 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/).
Cite this article
TY - CONF AU - Jianghao Huang PY - 2015/04 DA - 2015/04 TI - Network intrusion detection model based on genetic ant colony algorithm BT - Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering PB - Atlantis Press SP - 650 EP - 654 SN - 1951-6851 UR - https://doi.org/10.2991/amcce-15.2015.203 DO - 10.2991/amcce-15.2015.203 ID - Huang2015/04 ER -