Improving the Speed of the Network Intrusion Detection

被引：0

作者：

Sadeghi, Zahra ^{[1
]}

Bahrami, Asadollah Shah ^{[1
]}

机构：

[1] Guilan Univ, Dept Comp Sci, Guilan, Iran

来源：

2013 5TH CONFERENCE ON INFORMATION AND KNOWLEDGE TECHNOLOGY (IKT) | 2013年

关键词：

intrusion detection system; artificial immune system; negative selection; detection speed;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Currently with the increasing network attacks, intrusion detection systems (IDS) have became an ordinary component of network security. Artificial immune system (AIS) is a new bio-inspired model with some processes such as negative selection (NS). The NS is based on discrimination of self and non-self patterns which plays an important role for intrusion detection, so it is applied in this field. Since speed and accuracy of detection is the main goal of IDS, in this paper we proposed an improved algorithm for negative selection which will increase the speed of intrusion detection in networks. The experimented results prove the performance of the algorithm.

引用

页码：88 / 91

页数：4

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