Shulou(Shulou.com)06/03 Report--

Data security is one of the most important means to realize privacy protection. Data security is not an independent element, but needs to be together with network security, system security, business security and other factors. Only when all of them are done, can we finally achieve the effect of data security.

With the advent of the era of AI and DT, traditional enterprises pay more and more attention to data, and gradually begin to interconnect internal data. Its core is to connect the processes of various business systems through data integration and synchronization, and to create greater value through the secondary processing of data.

In essence, data, as a means of production, is added to the production process of enterprises and becomes an important source of energy. However, the data itself may bring all kinds of risks in the production process due to poor human management and poor control of the production process, and may export risks in the exported products and services. Such as large-scale data leakage caused by insiders, the risk of business system failure caused by data quality, and the exposure of personal privacy of products and services.

Therefore, we urgently need to establish a risk control system for data flow and use, and need a set of norms, data classification management system, scene control flow, traceability system, data risk identification and measurement system, and detection system. It is used to prevent all kinds of data risks caused by various internal production systems involving data and the non-standard behavior of personnel.

Let's move on to some of the pain points that need to be addressed when building a data security system:

01 data access risk

1. Lack of unified account management: big data has many components, each has its own set, and lacks a unified user account system.

2. Lack of identity authentication management: big data component authentication access identity is weak, lack of effective identity authentication means for big data access entrance.

3. Weak data authorization ability: lack of fine-grained authorization and fine-grained authority control and protection mechanism for data use.

02 data flow risk

1. Lack of audit traceability: big data component audit ability is weak, lack of comprehensive two-way audit traceability of data flow.

2. Weak data protection ability: lack of risk control and desensitization protection mechanism for data use and export.

03 risk of data operation and maintenance

The main contents are as follows: 1. The cost of data management is large: all kinds of data are aggregated, the amount of data is large and complicated, it is difficult to sort out data assets, and there is a lack of classification and classification means for sensitive data.

2. Lack of supervision of operation and maintenance behavior: system administrators and operation and maintenance administrators have huge authority, and their operation behavior lacks effective supervision and control as well as accountability ability.

3. Lack of control over high-risk operations: some specific high-risk operations are not intercepted, which can easily lead to the consequence of mistakenly deleting the database.

In view of the above pain points, Singularity Cloud DataSimba provides a complete set of big data risk management programs.

First of all, standardize big data's visitors and uniformly standardize access control.

1. Establish big data unified user management system to get through the original enterprise account system.

2. Establish a unified authentication management system for big data, and control the access entrance by multiple factors to prevent data streaking.

02 establish big data's resource management capabilities and standardize data authorization processes and means

1. To establish a query platform for unified management of data assets, it is necessary to carry out hierarchical and classified management of data.

2. Data access requires unified authorization of workflow approval to quickly complete the data business process.

03 control and protection of sensitive data access

1. Fine-grained permissions need to be set to control sensitive database tables, fields and files to be obtained by low-permission users.

2. Provide meticulous operation management and control means, and protect them based on data level, data label and data classification.

3. Provide transparent dynamic desensitization ability.

4. Control the frequency and volume of data accessed by users.

5. Control the high-risk operation of users.

04 control the risk of data export

1. Approve the export scenario based on sensitive data level and permissions.

2. Restrict the landing of development and export data, and export the data through a unified platform after examination and approval.

05 internal audit of internal personnel, analysis of abnormal behavior and tracing to the source of the incident

1. Audit, UBA analysis and traceability of big data administrator's operation behavior.

2. Audit, UBA analysis and trace back to the operation behavior of big data's development and analysis.

3. Audit, UBA analysis and traceability of the data export operation.

Singularity Cloud DataSimba can help enterprises establish a unified 4A management system (account, authentication, authorization, audit), help enterprises solve the problems of "what is there, where, how to manage and how to control", and then help enterprises to carry out big data sensitive data classification management, fine-grained authorization management, data desensitization protection management and so on.

Effectively supervise the data operation behavior of operation and maintenance, developers, BI and other personnel through security audit, improve the deterrent power of the platform by tracing the source, so that illegal personnel do not dare to carry out illegal operations such as data disclosure, build access baseline by means of risk control management, in-depth learning and analysis of big data's access behavior, and linkage intelligent interception rules to prevent illegal personnel from illegally accessing and operating data.

Finally, help enterprises to achieve overall control of the overall data flow and security situation, help enterprises to manage the risk points in data flow, and complete the visual, supervisory, controllable and manageable capacity building of the whole process of big data's safe use.

​

Welcome to subscribe "Shulou Technology Information " to get latest news, interesting things and hot topics in the IT industry, and controls the hottest and latest Internet news, technology news and IT industry trends.