网络数据流特定数据检测方法优化研究

Network Data Flow Specific Idetection Method Optimization Research

对网络数据流特定数据进行检测,在提高网络安全方面具有重要作用。由于网络数据流特征不能固定,使得网络数据流随时发生变化。传统的检测方法通常将网络数据流特定数据入侵视为一种非平稳的随机入侵行为,当入侵数据具有较强的干扰时,需要通过被忽略,导致检测性能差的问题。提出基于时频特征检测的网络数据流特定数据入侵检测算法,构建了网络数据流特定数据的信息流信号模型,进行了网络数据流特定数据入侵特征的抗干扰滤波设计和特征分析,采用时频特征检测算法实现了入侵数据的检测。仿真结果表明,改进算法能有效检测入侵特征的空间谱时频特征,提高对入侵信息数据的定位精度,对特定数据的检测性能较高。

A specific data intrusion detection algorithm of network data flow based on time- frequency feature detection was proposed in the paper. The signal model of the specific data information flow of network data flow was built to make the anti- jamming filter design and characteristic analysis for the characteristics specific data intrusion of network data flow. Time- frequency feature detection algorithm was used to realize intrusion data detection. The simulation results show that the improved algorithm can effectively detect the time- frequency features of spatial spectrum of intrusion characteristics,and increase the locating accuracy of intrusion information data,which has higher performance of specific data detection.