多频自适应共振检测病毒感染免疫性分析

Analysis of Immunity of Virus Infection Based on Multi Frequency Adaptive Resonance Detection

网络病毒感染的免疫性分析是提高网络安全性能的重要因素。由于网络病毒具有发散指向性,导致对网络病毒的感染免疫性分析建模困难。提出基于多频自适应共振检测的网络病毒感染免疫性分析模型,构建多路复用器输入输出的网络病毒感染模型,进行病毒信息特征预处理,得到用户约束对照多路复用状态下的病毒入侵干扰链路结构。根据自相关函数极限分离定理,在极向环空间内进行自相关成分分析,以代价函数最小化的形式进行病毒感染强度快速寻优分离,由此实现对病毒感染的免疫性分析模型构建。通过仿真实验结果表明,采用该算法,对网络在遭受病毒感染下的免疫控制性能较平稳,代价开销控制精度合理,网络波动被约束到了一个较小的范围,展示了方法优越的病毒感染限定和免疫性能。

The analysis of network virus infection immunity is an important factor to improve the network security performance. Because the network virus has spread performance, virus immunity analysis modeling is difficult to be constructed.An improved analysis model of immunity of network virus infection is proposed based on multi frequency adaptive resonance detection, the multiplexer input and output model of the network virus infection is constructed. The virus information feature preprocessing is taken, and the constraint control multiplexing condition virus interference link structure is obtained. According to the separation theorem of autocorrelation limit function, autocorrelation analysis is taken in the poloidal loop space. The cost function is minimized in the form of virus infection intensity fast optimizing separation, and the immune virus infection analysis model is constructed. The simulation results show that, this algorithm can make the network immune from viral infection control performance is more stable, cost control precision is reasonable. Network fluctuation is constrained to a smaller range, it shows better virus infection and limitation property.