李欣蔚, 陈辉, 张亚红. 自回归滑动平均和相关向量机的信息系统安全态势估计[J]. 微电子学与计算机, 2017, 34(9): 141-144.
引用本文: 李欣蔚, 陈辉, 张亚红. 自回归滑动平均和相关向量机的信息系统安全态势估计[J]. 微电子学与计算机, 2017, 34(9): 141-144.
LI Xin-wei, CHEN Hui, ZHANG Ya-hong. Information System Security Situation Assessment Based on Data Mining[J]. Microelectronics & Computer, 2017, 34(9): 141-144.
Citation: LI Xin-wei, CHEN Hui, ZHANG Ya-hong. Information System Security Situation Assessment Based on Data Mining[J]. Microelectronics & Computer, 2017, 34(9): 141-144.

自回归滑动平均和相关向量机的信息系统安全态势估计

Information System Security Situation Assessment Based on Data Mining

  • 摘要: 为了改善信息系统的安全态势估计效果, 提出了自回归滑动平均和相关向量机的信息系统安全态势估计模型(ARIMA-RVM).该模型收集大量信息系统安全的历史数据, 然后采用自回归滑动平均和相关向量机描述信息系统安全态势变化特点, 建立信息系统安全态势估计模型, 最后与其他信息系统安全态势估计模型进行了对比测试, 结果表明, ARIMA-RVM可以发现信息系统安全态势的变化趋势, 获得比其他模型更好的信息系统安全态势估计结果, 估计结果可以帮助信息系统安全管理者制定防范措施.

     

    Abstract: In order to estimate the effect of improving security situation information system, put forward the estimation model of information system based on data mining security situation. The method of collecting a lot of information system security of the historical data, and then using data mining combined kernel function to dig out the characteristics of information system security situation from the historical data, the establishment of information system security situation assessment model, finally model were compared, and the other information system security situation assessment results show that the model can be found to change the trend of information system security situation, get information system security situation better contrast model estimation results, the estimation results can improve the security of the information system and formulate corresponding preventive measures.

     

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