基于贝叶斯网络的云安全态势感知系统设计

Design of Cloud Security Situational Awareness System Based on Bayesian Network

为使差分后态势数据信号波形更贴合原始态势数据的波形分布形式,从而辅助网络主机实现对云数据参量的安全感知,设计基于贝叶斯网络的云安全态势感知系统。将云数据终端采集到的数据信息参量,按需分配至态势评估模块与态势预测模块之中,为网络主机提供一个相对稳定的硬件运行环境。在此基础上,根据贝叶斯网络连接情况,确定云数据权重值,再联合主机元件所采集到的运行数据,得到准确的态势值计算结果,结合相关硬件设备结构,完成基于贝叶斯网络的云安全态势感知系统设计。实验结果表明,与数据挖掘型感知系统相比,随着贝叶斯网络作用能力的增强,差分后态势数据信号的波动形式始终能够较好贴合原始态势数据的波动形式,对于网络主机而言,其对于云数据参量的安全感知能力确实得到了有效促进。

In order to make the differential situation data signal waveform fit the waveform distribution form of the original situ-ation data better,and thus assist the network host to realize the security awareness of cloud data parameters,a cloud security situa-tion awareness system based on Bayesian network is designed.The data information parameters collected by the cloud data terminal are allocated to the situation assessment module and the situation prediction module as required,so as to provide a relatively stable hardware running environment for the network host.On this basis,according to the connection situation of Bayesian network,the weight value of cloud data is determined,and then the accurate situation value calculation result is obtained by combining the opera-tion data collected by host components.Combined with the related hardware equipment structure,the design of cloud security situa-tion awareness system based on Bayesian network is completed.The experimental results show that,compared with the data mining perception system,with the enhancement of Bayesian network's function ability,the fluctuation form of the differentiated situation data signal can always fit the fluctuation form of the original situation data better,and for the network host,its security perception ability of cloud data parameters has been effectively promoted.