Research And Implementation Of SaaS Cloud Service Data Automatic Extraction And Security Monitoring

With the maturation and popularization of cloud computing,the proportion of commercial applications using SaaS as the delivery mode is increasing day by day.Meanwhile,the importance of cloud security and SaaS security has a significant growth.The process when users using SaaS applications will produce massive data.The way to protect the user's data security and personal privacy in SaaS service,has become a concern in the industry.SaaS service providers often use the method of data monitoring to ensure the security and integrity of data.The existing data monitoring methods are mostly carried out in the first party,and it is a problem to individual adapting multiple different application.When the data need to be provided to data analysts or testers,for protecting the user's privacy,the service providers often mask or obscure the data to avoid that user's identity is accurately recognised and other issues.Most of the existing data masking plans are designed by the service providers and this way hampers the data fusion.To solve the above problems,through the research of domestic and foreign in this field,the paper proposes and implements a third party based,SaaS data monitoring and masking method with high automation and adaptation:1)Using browser rendering based automated crawler technology,automatic analysis,identify and comprehensive collect different SaaS application page links.2)According to the different types of application pages,propose different data extraction algorithm to automatic extract different page data:For the repeated pattern based pages with items,use tree alignment algorithm for data extraction;for the title-body format based pages with theme use path ratio algorithm for data extraction.3)After successfully obtaining the data from different SaaS applications,design the data function module,and do further processing for the data.In this paper,the medical big data system is used as the experimental subjects.The data of various medical systems are extracted and monitored completely.Experiments show that the contribution of this paper is well worked for automatic adapting different SaaS application and accurately obtaining the application data,and effectively and conveniently solves the problem of multiple application data monitorin,and it has important value to research and develop.