Integrated artificial immune system for intrusion detection

被引：0

作者：

Chen, Yue-Bing ^{[1
]}

Feng, Chao ^{[2
]}

Zhang, Quan ^{[2
]}

Tang, Chao-Jing ^{[2
]}

机构：

[1] No. 61 Research Institute of General Staff, Beijing 100141, China

[2] School of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China

来源：

Tongxin Xuebao/Journal on Communications | 2012年 / 33卷 / 02期

关键词：

Feature extraction - Cells - Immune system;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

According to the practical requirements of intrusion detection, an integrated arti?cial immune system (IAIS) was proposed. The system combined dendritic cell algorithm (DCA) and negative selection algorithm (NSA). DCA was used to detect behavioral features. NSA was used to detect structural features. IAIS was validated on KDD 99 dataset. Comparisons to other approaches were made. The experimental results show that the detection performance of IAIS is comparable to classic classification algorithm. IAIS does not rely on labeled data to train detectors. It combines behavioral features and structural features to detect intrusions in real-time mode.

引用

页码：125 / 131