基于哈希锁定的网络传输异常序列监测仿真

为有效提升传统网络传输异常序列监测方法的处理效率,提出基于哈希锁定的网络传输异常序列监测方法。利用随机投影的哈希函数将高维空间数据转换为低维空间数据,并利用网络传输序列的多元数量值函数,组建网络传输结构模型。对网络传输结构模型进行流量时频采样以及时间序列分析,结合FIR滤波器对其进行流量抗干扰处理,通过高阶累计的振荡衰减,对输出的滤波数据进行特征搜索及提取,实现基于哈希锁定的网络传输异常序列监测。仿真结果表明,所提方法具有较强的抗干扰性,并且能够确保网络的稳定运行。

Hash-Locked Network Transmission Anomaly Sequence Monitoring Simulation

In order to effectively improve the efficiency of the traditional method, this article put forward a method of monitoring abnormal sequence in network transmission based on hash locking. The hash function of random projection was used to convert high-dimensional spatial data into low-dimensional spatial data. Then, the network transmission structure model was built by the multivariate quantity function of network transmission sequence. The traffic time-frequency sampling and time series analysis was conducted on the network transmission structure model. Combined with FIR filter, the traffic anti-interference processing was carried out. Through the high-order cumulative oscillation attenuation, the feature search and feature extraction of output filter data were carried out. Thus, the monitoring of abnormal sequence in network transmission based on hash locking was achieved. Simulation results show that the proposed method has strong anti-interference ability and it is able to ensure the stable network.