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基于信息融合度传递的频域徙动入侵特征挖掘算法
引用本文:米晓萍,李雪梅.基于信息融合度传递的频域徙动入侵特征挖掘算法[J].计算机科学,2015,42(3):224-227, 232.
作者姓名:米晓萍  李雪梅
作者单位:山西大学计算机工程系 太原030013
基金项目:本文受山西省自然科学基金项目(2011011014-3)资助
摘    要:在功率自激混合组合网络中,路由之间的相群特征相异性会产生谐振信号,因此需要有效挖掘入侵信号的频域徙动特征来实现对入侵信号的拦截。传统方法采用混合蛙跳算法挖掘入侵特征并且聚类中心矢量向模糊边缘贴近,因此搜索和挖掘精度不高。提出了一种基于混合蛙跳最优模因组信息融合度传递的频域徙动入侵特征挖掘算法。构建功率自激组合网络的系统模型和入侵信号数学模型,基于频域谐振慢变衰落幅度均衡原理,得到多源网络攻击源信号在相干点积功率累积尺度坐标,采用多普勒频移模糊搜索对入侵信号进行平滑处理,计算入侵信号的多普勒频移状态空间固有模态函数,得到入侵信号的频域特征包络幅度估计值。采用IIR滤波算法,对信号进行降噪滤波处理,提高信号的纯度,提出基于信息融合度传递的混合蛙跳入侵信号检测算法,优化特征挖掘结果,完成入侵信号的频域徙动特征挖掘算法改进。仿真实验结果表明,该算法能准确挖掘入侵信号的频域徙动特征,特征的波脊亮点明显,在低信噪比下提高了入侵信号的检测性能。

关 键 词:混合蛙跳算法  频域徙动  数据挖掘  网络

Mining Algorithm of Frequency Domain Migration Intrusion Feature Based on Information Fusion Transfer
MI Xiao-ping and LI Xue-mei.Mining Algorithm of Frequency Domain Migration Intrusion Feature Based on Information Fusion Transfer[J].Computer Science,2015,42(3):224-227, 232.
Authors:MI Xiao-ping and LI Xue-mei
Affiliation:Department of Information Engineering,Shanxi University,Taiyuan 030013,China and Department of Information Engineering,Shanxi University,Taiyuan 030013,China
Abstract:In the power self incentive networks, the difference property of routing phase group characteristics produces resonance signal,therefore frequency domain migration feature needs to be mined for intrusion signal interception.Traditional methods use shuffled frog leaping algorithm for data mining,and the clustering center vector is close to fuzzy edge,resulting in low search and mining accuracy.An improved mining algorithm of frequency domain migration intrusion feature was proposed based on shuffled frog leaping optimal mode information fusion transfer.The power self combination network system model and mathematical model of intrusion signal are constructed.On the basis of frequency resonant slow fading amplitude equalization principle,the multi-source network attack source signals in the coherent point integrated power accumulation scale coordinate are obtained.The Doppler frequency shift fuzzy search algorithm is used for intrusion signal smoothing processing.The intrusion signal state space modal function of Doppler frequency shift is calculated.Amplitude estimation value is obtained.IIR filtering algorithm is used for signal filtering processing to improve the signal purity.The shuffled frog leaping intrusion detection algorithm based on information fusion of transfer is obtained.Feature mining results are optimized.The frequency domain migration intrusion signal feature mining algorithm is completed.The simulation results show that the algorithm can accurately mine the frequency domain migration feature of intrusion signal.The wave ridge highlight is obvious,and it can improve the detection performance of the intrusion signal in low SNR.
Keywords:Shuffled frog leaping algorithm  Frequency domain migration  Data mining  Network
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