基于模糊Petri网的误用入侵检测方法

Method of Misuse Intrusion Detection Based on Fuzzy Petri Nets

  • 摘要: 提出了基于模糊Petri网的误用入侵检测方法,并将类似于神经网络的学习引入模糊Petri网,以调整攻击知识模型参数.理论分析表明,基于模糊Petri网的误用入侵检测系统具有更高的推理效率,能从环境中动态学习调整知识模型的相关参数,如阈值、权值、确信度.仿真结果表明,在大多数情况下,学习调整后的知识模型能够提高误用检测系统的检测率.

     

    Abstract: A method of misuse intrusion detection based on fuzzy Petri nets is proposed,and the learning ability similar to neural networks introduced into fuzzy Petri nets to adjust the parameters of attack knowledge model.Analysis indicated that,in the misuse detection system based on fuzzy Petri nets,the reasoning efficiency seemed to be improved,and the parameters such as threshold,weights and belief strength can be learned from the environment dynamically.Test results displayed that,under most circumstances,system detection rate was increased when the attack knowledge model was adjusted after learning.

     

/

返回文章
返回
Baidu
map