Sensitive data refers to sensitive data that may bring serious harm to society or individuals after being leaked. Including personal privacy data, such as name, ID number, address, telephone number, bank account number, e-mail address, password, medical information, education, etc. It also includes data that should not be published by enterprises or social organizations, such as the operation of enterprises, the network structure of enterprises, and the list of IP addresses.
There are two technical routes for desensitization of sensitive data, one is static desensitization, and the other is dynamic desensitization. Then, sensitive data is found by combing data assets, and sensitive data in the database is deformed to prevent sensitive data from leaking.
According to the above data security governance concept, only by properly handling the use and security issues of data assets can the government and enterprises develop steadily and rapidly in the new data era, focusing on data permissions and data application scenarios around the core goal of "making data use safer" to help users complete the construction of data security governance system.
Data security governance is not the construction of a single product or platform, but the construction of a data security governance system covering all data usage scenarios. Therefore, it needs to be done step by step and in stages. Data security governance is not a project, but a project. In order to effectively practice data security governance and form a closed loop of data security, we need a systematic process to complete the construction of data security governance.