引入偏移量递阶控制的网络入侵HHT检测算法

在强干扰背景低信噪比下对网络潜质入侵信号的准确检测是决定网络安全的关键。传统的Hilbert-Huang变换(HHT)入侵信号检测算法在求解入侵信号的瞬时频率特征时,因包络线失真引起的边界控制误差,会造成频谱泄漏,从而导致检测性能较差。提出了一种基于时间-频率联合分布特征和偏移量递阶控制HHT匹配的网络入侵信号检测算法,即构建网络潜质入侵数学演化模型,把复杂的入侵信号分解成IMF单频信号,得到入侵检测系统的状态转移方程,基于Hilbert变换对入侵信号进行离散解析化处理,构建入侵信号解析模型。对每个入侵信号经验模态分解后的解析模型IMF分量用Hilbert变换进行谱分析,通过递阶控制调整HHT频谱偏移,将残差信号投影与入侵信号的Hilbert边际谱进行匹配,减小包络线失真引起的边界控制误差,抑制频谱泄漏,实现对入侵信号的精确检测和参数估计。实验表明,该算法进行网络入侵信号检测时,具有较强的抗干扰性,能从低信噪比背景下有效检测出入侵信号,检测性能有较大提高。

Network Intrusion Detection Algorithm Based on HHT with Shift Hierarchical Control

In the strong interference background and low signal-to-noise,the accurate detection of network intrusion potential signal is the key of network security.The traditional Hilbert-Huang transform (HHT) intrusion signal detection algorithm has boundary control error resulted from envelope distortion,and spectrum leakage is occurred which leads the bad detection performance .An improved detection algorithm was proposed based on the time-frequency distribution feature and offset hierarchical control network HHT matching.The network potential intrusion mathematical evolution model is constructed,and the complex signals are decomposed into IMF single frequency signal.The intrusion detection system state transfer equation is obtained.The discrete analytical processing of the intrusion signal is taken based on Hilbert transform,and the signal model is obtained.The intrusion signal is decomposed with empirical mode,and the IMF component is analyzed by Hilbert spectrum.The HHT frequency shift is adjusted by hierarchical control mechanism,and residual projection and intrusion signal Hilbert marginal spectrum are matched.The envelope distortion is reduced,and the spectral leakage is suppressed.The accurate detection and parameter estimation of intrusion signal are achieved.Experiments show that this algorithm has strong anti-interference performance in intrusion signal detection,which can detect intrusion signal with low SNR effectively,and the performance of detection is improved.