摘要
恶意干扰下的网络病毒信息具有较强的高斯随机性和带宽性,传统的时频分析方法及小波特征检测方法难以实现对该类病毒入侵的有效检测。提出一种基于盲频谱检测的恶意干扰下网络病毒检测算法。构建了恶意干扰下的网络病毒入侵的信号模型构建,采用高斯平滑滤波算法进行干扰抑制预处理,提取滤波后的恶意干扰下病毒数据的盲频谱特征,以此为数据基础实现对网络入侵的准确检测。仿真结果表明,采用该文算法进行网络病毒检测识别准确度较高,性能优越,保障了网络安全。
The information of the network virus with malicious interference has strong Gauss random and bandwidth, the traditional time-frequency analysis method and wavelet feature detection method is difficult to achieve the effective detection of the virus intrusion. A new detection algorithm of network virus based on blind spectrum detection is proposed. The signal model of network virus intrusion is constructed, and the interference suppression is used to extract the data from the filtered malicious interference. The method is used to realize the accurate detection of network intrusion. The simulation results show that the proposed algorithm has higher accuracy and better performance, which ensures the security of the network.
出处
《科技通报》
北大核心
2016年第4期134-138,共5页
Bulletin of Science and Technology
基金
河南省自然科学基金研究项目资助(152300410145)
关键词
网络病毒
盲频谱
信号
检测
network virus
blind spectrum
signal
detection
