As a data-intensive industry, banking needs data support in customer portrait construction, risk prevention and control, efficiency optimization and other businesses, because the guarantee of data security is the bottom line of banking business development. It is imperative to promote the implementation of enterprise’s data security management. However, the rural financial institutions under the Rural Credit Cooperative have numerous outlets and are widely distributed, and carry out extensive business cooperation with plenty of local institutions and customers in villages and towns. Compared with large commercial banks, the business environment of rural financial institutions is more open, the business ecology is more complex, and the data security management is more complex, open and multi-sourced.
TDMP V3.0 independently designed and developed by Digital China is a professional-level data masking system based on B/S architecture, the most popular Spring MVC and Mybatis framework technology, which provides professional data security programs with high security, availability, reliability, stability and efficiency for data privacy protection of enterprises. By supporting both static and dynamic masking algorithms, it has powerful automatic sensitive data discovery function and parallel processing engine, and has the characteristics of flexible data masking strategies, accurate privacy data discoveries, diversified masking methods, efficient processing algorithms, rigorous process approvals, detailed audit reports and perfect monitoring systems. It provides a variety of data masking methods such as deformation, shielding, replacement and encryption according to the demand of the whole business scenario, and monitors the data masking server resources in real time to provide users with traceable security audit.
After the processing of Digital China’s TDMP V3.0, the business data maintains high emulation, consistency and inheritance of source data distribution characteristics, to continue to meet the use demand of different application scenarios, such as association analysis, machine learning and real-time query.