Research On Key Technologies Of Data Masking Based On The Sensitive Data Of P2P Lending

In recent years,with the rapid development of social networking platform,the communication channels between people become more and more convenient and extensive,which involved the financial business also appeared in the trend of off-network [1-2],the Internet financial era is coming.China's Internet financial development process is much shorter than the United States and Europe and other developed economies,but the pace of development is very alarming,and has shown a wide range of business models and operating mechanisms.For example,crowdfunding,P2 P Lending,third-party payments,and big-data financial,which have shown an explosive growth trend.In particular,P2 P Lending,from scratch,in 7 years the total volume reached 1 trillion yuan,then in next 7 months exceeded 2 trillion,and another 5 months the volume break through 3 trillion.In the process of rapid business growth,Massive user information is collected,stored,analyzed and used,which contains personal social network information,personal identity information,personal financial information and many other sensitive content.Because it is a combination of financial and IT high-risk industries,It has the natural high-risk,so that the information security and privacy protection become more and more public concerned.This paper focuses on the Data Masking of sensitive data of the P2 P Lending users,and we analyze the characteristics and shortcomings of traditional technologies in Data Masking,for example,shuffling,numerical transformation,encryption and empty technologies,etc.Then we propose the range extended-fuzzy,Fence,single attribute generalization and other new improvement methods.And then we use the new method to P2 P network user Data Masking.In view of the problem of Big data masking,this paper designs a Hadoop platform format-preserving encryption solution,and completed the system implementation.