Data Management (DMS) provides the sensitive data protection feature. You can use the feature to scan the metadata of a database for sensitive data. Then, you can de-identify and manage the sensitive data.

Supported databases

  • Relational databases
    • MySQL: ApsaraDB RDS for MySQL, PolarDB for MySQL, and MySQL databases from other sources
    • SQL Server: ApsaraDB RDS for SQL Server and SQL Server databases from other sources
    • PostgreSQL: ApsaraDB RDS for PostgreSQL, PolarDB for PostgreSQL, and PostgreSQL databases from other sources
    • MariaDB: ApsaraDB RDS for MariaDB TX and MariaDB databases from other sources
    • PolarDB-O
    • PolarDB-X
    • OceanBase
    • Oracle
    • DB2
    • Dameng (DM)
  • Data warehouses
    • AnalyticDB for MySQL
    • AnalyticDB for PostgreSQL
    • Data Lake Analytics (DLA)
    • ClickHouse
    • MaxCompute

Feature architecture

The sensitive data protection feature helps you effectively detect and protect sensitive data assets in your enterprise. This prevents sensitive data from being abused or leaked. The following figure shows the architecture of the sensitive data protection feature.

Feature architecture

Features

  • Sensitive data dashboard: DMS provides a sensitive data dashboard that helps an enterprise manage sensitive data in a centralized manner.
  • Automated metadata scan
    • DMS allows you to customize a schedule for scanning data.
    • DMS can automatically detect and classify sensitive data. This helps you effectively detect and manage sensitive data.
    • DMS supports built-in and custom data classification templates to implement fine-grained classification and management of sensitive data. You can manage sensitive data based on the principle of least privilege.
  • Sensitive data de-identification
    • DMS supports built-in and custom sensitive data de-identification rules. This helps you flexibly manage sensitive data de-identification algorithms. You can de-identify different fields based on your business scenarios, implement fine-grained permission control, and ensure least sensitive data exposure.
    • DMS provides a test environment that allows you to experiment with your sensitive data detection and de-identification rules.
    • DMS allows you to manage the access of users and applications to sensitive data.
  • Sensitive data monitoring: DMS monitors the use of sensitive data, audits anomalous activities, and generates alerts. This helps you trace anomalous activities and the source of data leaks.

Terms

  • Sensitivity level: Certain business data, such as mobile numbers and ID card numbers, is sensitive. The fields that store sensitive data must be encrypted before they are displayed during regular queries. DMS supports the following three sensitivity levels based on the sensitivity of the data:
    • Low Sensitivity: The Low Sensitivity level is derived from the Internal level of DMS. For a database instance that is managed in Security Collaboration mode, the sensitivity level of the data stored in the database instance is Low Sensitivity by default.
    • Moderate Sensitivity: The Moderate Sensitivity level is derived from the Sensitive level of DMS.
    • High Sensitivity: The High Sensitivity level is derived from the Confidential level of DMS.
    Note After you set the sensitivity levels for data, take note of the following rules:
    • When you query data in the SQLConsole, the Moderate Sensitivity and High Sensitivity fields on which you have no permissions are displayed as strings of asterisks (*) or in a custom manner.
    • To query, export, or change Moderate Sensitivity or High Sensitivity fields, you must apply for the permissions on these fields.
    • A database administrator (DBA) or DMS administrator can configure special approval processes for exporting or changing data that contains Moderate Sensitivity or High Sensitivity fields.
  • Detection rule: DMS provides built-in sensitive detection rules that are designed for different industries based on the relevant laws and regulations. You can also customize detection rules that detect sensitive data based on the metadata of a database or the data that is stored in the database.
  • Data types: DMS provides data types that are defined based on various laws and regulations. You can also create custom data types.
    • Level 1 data types: include types such as personal information, enterprise information, and location information.
    • Level 2 data types: include types such as mobile phone numbers, email addresses, and bank card numbers.
  • De-identification algorithm: DMS supports hash, redaction, substitution, rounding, and encryption algorithms to de-identify data. You can flexibly configure de-identification rules based on the built-in de-identification algorithms.
  • De-identification policy: DMS generates a de-identification policy after you configure a de-identification rule for the selected sensitive fields.

References