Research And Implementation Of Privacy Index Method In Big Data Environment

Big data mining and analysis is the basis for achieving big data values,and big data query is the basis of big data analysis,all big data mining and analysis techniques need to be achieved through big data queries.However,in the era of big data,the storage structure,intrinsic relationship and access methods of data have undergone great changes.The data is mainly stored in the key-value mode,while most query index structures are searched by key,which can not effectively support non-key search mode.Therefore,in order to satisfy the user's diverse query requirements and improve the efficiency of data query processing,it is necessary to create an index structure based on non-key as the keyword in big data management system.But,non-key attributes often contain sensitive information of data,preventing the disclosure of sensitive information is a basic requirement of query and data analysis,however,in the big data query,the existing data privacy protection technology is often difficult to effectively apply.Based on the typical characteristics of the big data environment,this paper analyzes and models the storage structure and query mode of big data in order to solve the problem of user query privacy leakage and the data privacy disclosure of data owners in the process of quering sensitive information.This paper uses encryption algorithm to design a sensitive information storage structure-SILL.Combined with the structure of SILL presents a new non-key query PP-Tree index structure has to protect sensitive information of keywords,and the design of PP-Tree query method based on the data,the data privacy and user query privacy protection target.In this paper,the fast query for non-key is implemented to protect the sensitive information from being leaked,and the efficiency of sensitive information query is improved.Theoretical analysis and test results show that the proposed PP-Tree index structure can effectively improve the query efficiency of non-key in the premise of protecting sensitive information from being leaked,and the accuracy rate is 98%.The research of index provides a theoretical method and technical means for privacy protection in large data query,and is of great significance to promote the healthy and rapid development of big data industry.