The masked data remains consistent over time. It is suitable for scenarios where data consistency is essential.
Dynamic Data Masking (DDM)
Dynamic masking involves real-time masking of sensitive data. The original data remains unchanged in storage. It is often used in production environments to protect sensitive data from unauthorized access. It only allows authorized users to see the unmasked data.
Tokenization
Tokenization replaces sensitive data with sweden whatsapp number data randomly generated tokens or reference values. The actual sensitive data is stored in a separate token vault. Tokenization is suitable for scenarios where retaining data format and structure is important. The original data must be securely stored separately.
Tokenization offers a high level of security, as the original data is not present within the application or database. But it can be retrieved when needed from the token vault.
Effective data masking involves various techniques and best practices. The end goal is to ensure that sensitive information remains secure. Here are some of the most common data masking practices:
Redaction
Redaction is selectively removing or obscuring sensitive information from documents or records. This practice is often used in legal and government contexts to protect confidential information.