Massive data security feature extraction algorithm based on visualization technology
Due to the poor application effect of traditional algorithms in the extraction of massive data security features,not only the extraction error is relatively large,but also the extraction time is relatively long,which cannot achieve the expected feature extraction effect,and a massive data security feature extraction algorithm based on visualization technology is proposed.In the network log record set,the massive data related to the data extraction source is picked up,the cluster analysis method is used to cluster and analyze the massive data,the security features of massive data are identified by the reliability of the data,and the security features are statistically extracted by the visualization technology,so as to complete the extraction of massive data security features based on visualization technology.Experiments have shown that the data security feature extraction error of the design method is less than 1%,and the extraction time is less than 1s,which can effectively ensure the accuracy and speed of extracting the security features of massive data.
NETL
NSTL
万方数据
