摘要
基于群体人工免疫的入侵检测模型主要由一些离散的元素组成,这些元素之间没有直接的交互。针对该问题提出一种基于人工免疫网络的入侵检测模型。该模型通过免疫网络中各元素之间的相互刺激作用而构成一个动态的平衡系统,以适应不断更新换代的网络攻击。实验结果表明,该模型可以较好地检测异常的网络数据包,具有较好的自适应性。
The intrusion detection model based on the population artificial immune is composed of discrete elements among which are no direct interactions. To solve this problem, this paper proposes a model which is based on the immune network. In this model, a dynamic balance system is constituted by the mutual stimulation among different elements, so it can adapt to the continuously updating of the attack. Results show that this model can detect abnormal data packets well, and has a better self adaptability.
出处
《计算机工程》
CAS
CSCD
北大核心
2009年第8期161-163,共3页
Computer Engineering
基金
山西省高校科技开发基金资助项目(200512G2)
山西大学科研基金资助项目(2005103)
横向科研基金资助项目
关键词
免疫网络
入侵检测
种群更新
权重修正
immune network
intrusion detection
population renewal
weight correction
