Sensitive Data Discovery and Protection (SDDP) detects and de-identifies sensitive data to help you precisely recognize and protect sensitive data.

Detect sensitive data and mark it with risk levels

SDDP can detect sensitive data in a large amount of data and accurately distinguish sensitive data from non-sensitive data. You can use the built-in algorithms of SDDP or create custom rules to scan your data assets that store structured data or unstructured data. SDDP then helps you classify data for further protection, such as fine-grained access control and storage encryption.

Detect data leaks to protect data

SDDP uses an intelligent detection model to analyze access of Alibaba Cloud accounts or external users to sensitive data. If a risk is detected, SDDP sends an alert to your data security team. This helps you improve risk prediction and prevention capabilities.

De-identify sensitive data

SDDP supports built-in and custom de-identification algorithms. You can use these algorithms to de-identify sensitive data in the production environment before transferring the sensitive data to other environments such as the development and test environments. This protects the security of sensitive data and ensures that the de-identified sensitive data is still usable in other environments.

Comply with the requirements on personal information protection

SDDP can accurately distinguish personal data from other data and protect personal data to avoid compliance issues.

Meet requirements of GDPR

SDDP can detect sensitive data in a large amount of data and allows you to audit the use of sensitive data. This allows you to meet the General Data Protection Regulation (GDPR) requirements for sensitive data protection.

Check data security compliance

In response to the requirements of relevant supervision departments for checking data security compliance, SDDP provides features regarding data security, such as sensitive data classification, data leak detection, and data de-identification, to help you achieve data security compliance.