基于因素神经网络的入侵检测模型

摘要

通过对网络攻击和防御的分析，提出一种基于因素神经网络理论（ FNN）的入侵检测模型，描述入侵检测模型的结构和工作流程，将解析型因素神经网络和模拟型因素神经网络结合起来，解决对复杂入侵行为建模难的问题。通过实验对模型进行验证，实验表明该模型对已知入侵行为检测的准确度高，对未知入侵行为也能做出准确的判断。%Through the analysis of network attack and defense , a model of intrusion detection based on the theory of factor neural networks ( FNN) is proposed .The structure and the working process of intrusion detection model are described .Combined with the analogous factor neural networks , the analytic factor neural networks can solve the problem of modeling for complex intrusion behavior .Finally an experimental verification of the model is given , which proves that the model of network intrusion detection with high accuracy can accurately judge the known and unknown intrusion behavior .