Science and technology innovation is deeply integrated into the financial business, the ever-changing trend of the basic environment, increasingly stringent regulatory trends, the emergence of endless technological trends, in the era of fintech 3.0, faced with the problem of data security:
1、Financial institutions keep a huge amount of core confidential data, the "value" of its existence caused by internal or external criminals covet;
2、The value of massive data needs to be further explored and enhanced in circulation, integration and sharing, but it also faces the risk of sensitive data leakage;
3、Most of the development, operation and maintenance work is undertaken by third-party personnel, making it difficult to control.
Data security protection in the financial industry needs to start from the top-level design idea of "one center, four systems, and six processes", build a financial data security protection center, and realize the security protection of the whole life cycle of financial data from the four dimensions of organization, management, technology, and operation.
1、Assist in building the data security management organization and management system of financial institutions, such as: data classification and grading guidelines, data sharing specifications, etc;
2、Financial data asset sorting and classification and grading, through research and automated technology implementation, to realize financial business data classification and grading, and to clarify data categories and levels, in order to formulate more accurate protection strategies;
3、Database auditing, database firewall, etc., according to different user rights in real-time control of all kinds of high-risk operations;
4、Data desensitization, application desensitization, data watermarking, etc., de-privatization of sensitive data in various scenarios such as data sharing, exchange, use, etc., adding data watermarks to protect sensitive data at source;
5、Data security integrated governance platform, the use of AI, big data intelligent modeling, unified analysis of various types of data security risks, posture display, the establishment of data security joint prevention and control capabilities to enhance operational efficiency.
1、Data management capacity enhancement: sound data asset inventory, implementation of data classification and grading, and realization of unified data marking; formulation of data security system, identification of data security risks and risk scenarios;
2、Data monitoring capability enhancement: conduct effective behavior identification, monitoring and early warning, discover data security events in time, and establish security measures for reinforcement;
3、Data control capability enhancement: for different business personnel, control the type of data accessed, access volume, access frequency, etc., and standardize the management of data assets in testing, development, production, sharing and other environments;
4、Data security operation capability enhancement: forming data security situational awareness, joint defense and control system through the data security comprehensive governance platform, breaking data security silos, and enhancing operational efficiency.
The use of big data, AI analysis and other technologies, can quickly learn modeling of data security issues, behavior prediction.
Flexible and open platform architecture, can continue to connect and enrich the security capability unit, in-depth correlation, mining all kinds of hidden risks, security posture comprehensive awareness.
Ystematic design, the formation of a unified joint defense and control data security prevention and control system, can deal with complex data security threats.
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