Research On The Key Technology Of Automated Discovery Of Enterprise Sensitive Information

In recent years,with the rapid development of informatization,the total amount of data created and maintained by various enterprises and organizations has achieved remarkable growth,and the data environment is becoming more and more complicated.The data is usually diverse and varied,and those valuable,sensitive data may be distributed to different data warehouses in the internal network,getting managers into trouble having a complete grasp of the data distribution.However,since it can be used to identify potential risks,to deal with the regulation of relevant law,and to selectively make protection for data in the case of limited resource,it is necessary for managers to know the storage mode,type and sensitivity of data.This problem involves analysis of data source and information sensitivity.At present,the research related to this problem mainly focuses on the mining of the specific contents of databases,but this thesis will focus on the identification of the data table category,and the way to describe the distribution of data in complex data networks.The main work of this research is:1.According to the existing research of information classification method and definition approach of sensitive information,the concept of "content element space" is proposed,as well as the approach to summarize the content element space.At the same time,a grading standard of information sensitivity is proposed,which is graded according to the magnitude of the likelihood of infringing the interests of individuals and organizations in the condition of information disclosure and the severity of the damage.2.The technology related to data mining is introduced and analyzed,and based on the Apriori algorithm,a method is proposed to identify the data table category,which discussed the process of the classification,and way to preserve the formatted results obtained by the method.3.According to the information classification and identification method proposed in this thesis,a set of sensitive information automatic discovery system based on this method is designed and implemented.The system consists of two parts,one is used to collect and analyze the relevant information from the heterogeneous data sources which called probe subsystem;the other named collect subsystem is used to summarize all the analysis results uploaded by numerous client subsystems,and display to user the distribution situation of the data with diagram.