网络入侵时间存在较强的无序性，与网络受损的关系比较复杂。传统的方法只能通过简单的线性关系对两者之间的关系进行描述，一旦入侵时间复杂程度增加，将会造成入侵时间非线性关联性急剧增加，导致模型的可信度降低。通过提取出模糊的网络受损特征，网络能够在较短时间内识别受损的网络。提出以粒子滤波为基础的模糊网络受损特征优化提取方法，通过粒子滤波独立分析成分的原则，进行粒子滤波联合函数的设计，把模糊网络受损信号分段分成一些局部进行分析考察，实现模糊网络受损特征的优化粒子滤波提取。结果表明，采用该算法能有效提高对模糊网络受损特征的正确识别率，性能优越，在网络安全领域中的应用价值较大。%The network intrusion time has strong disorder performance,and the relationship between it and network damage is complicated. The traditional method can describe the relationship between them by means of the simple linear relationship. Once the invasion time complex degree is increased,it will increase the nonlinear correlation of the invasion time sharply and re⁃duce the reliability of the model. The fuzzy network damage feature is extracted to identify the damage network within a short time. A fuzzy network damage feature optimization and extraction method based on particle filtering is proposed. The particle fil⁃tering joint function was designed by means of the independent analysis component principle of the particle filtering. The fuzzy network damage signal is segmented into some local parts for investigation and analysis. The optimal particle filtering of the fuzzy network damage feature is extracted. The results show that the algorithm can improve the correct recognition rate of the fuzzy network damage feature effectively,has superior performance and great application value in network security field.
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