基于SimHash算法的大数据网络安全态势的评估

Evaluation of big data network security situation based on simhash algorithm

在网络数据量日益增大及维度逐渐升高的背景下,为了更好地解决传统网络安全态势评估模型存储量小、执行率低的问题,构建了基于SimHash算法的安全态势评估模型。首先对大规模的网络进行划分,得到多个网络模块;然后预处理安全要素数据,将处理结果存储在大数据平台中;最后利用SimHash算法进行节点安全态势评估,基于节点与模块权重获取模块和网络的实际安全态势数据信息。实验结果表明,算法可准确、实时评估网络安全态势,为大数据领域的网络安全态势评估提供了一种新的方法。

Under the background of the increasing amount and dimension of network data,increasing amount of data generated by network security equipment and gradually increasing dimension,in order to realize effective response to the problems of small storage and low execution rate of traditional network security situation assessment model,based on the pre-processing of node security situation elements,this paper proposes a big data network security situation assessment model based on simhash algorithm.In the application process,firstly,the large-scale network is divided into several network modules,and then the security element data is preprocessed.After the preprocessing,the data is stored in the big data platform,and SIM is used.Hash algorithm is used to evaluate the security situation of nodes.Based on the weight of joint nodes and modules,the security situation of modules and networks is obtained.The results show that the algorithm can accurately evaluate the network security situation,and provides a new method for big data network security situation assessment.