基于混沌PSO算法优化RBF网络入侵检测模型
기우혼돈PSO산법우화RBF망락입침검측모형
Based on Chaos PSO algorithm optimize RBF network intrusion detec-tion
  • 万方数据
    计算机工程与应用 계산궤공정여응용
    COMPUTER ENGINEERING AND APPLICATIONS
    2013年 10期 84-87 ,共4页

    王亚%熊焰%龚旭东%陆琦玮

    왕아%웅염%공욱동%륙기위

    入侵检测模型%特征选择%粒子群优化算法%神经网络%混沌扰动%数据集 入侵檢測模型%特徵選擇%粒子群優化算法%神經網絡%混沌擾動%數據集
    입침검측모형%특정선택%입자군우화산법%신경망락%혼돈우동%수거집
    intrusion detection model%feature selection%particle swarm algorithm%neural network%chaos perturbation%datasets
    针对网络安全中异常入侵检测,给出了一种构建最优神经网络入侵模型的方法.采用混沌扰动改进粒子群优化算法,优化径向基函数RBF神经网络入侵模型.把网络特征子集和RBF神经网络参数编码成一个粒子,通过粒子间的信息交流与协作快速找到全局最优粒子极值.在KDD Cup 99数据集进行仿真实验,实验数据表明,建立了一种检测率高、速度快的网络入侵检测模型.
    침대망락안전중이상입침검측,급출료일충구건최우신경망락입침모형적방법.채용혼돈우동개진입자군우화산법,우화경향기함수RBF신경망락입침모형.파망락특정자집화RBF신경망락삼수편마성일개입자,통과입자간적신식교류여협작쾌속조도전국최우입자겁치.재KDD Cup 99수거집진행방진실험,실험수거표명,건립료일충검측솔고、속도쾌적망락입침검측모형.
    For anomaly intrusion detection in network security, this paper proposes a method of establishing the optimal neural network intrusion model. It improves particle swarm optimization algorithm by chaos perturbation. And it optimizes Radial Basis Function(RBF)neural network intrusion model. The subset features of network and RBF neural network parameters are considered as a particle. It uses the inter particle exchange of information and collaboration to find the global optimal particle extremum quickly. The simulation experiment is carried out on KDD Cup99 datasets. The simulation results show that it is a high detection ratio and fast speed network intrusion detection model.
    원문보기 원문다운로드 사이트로이동
저자의 최근 논문