How does data masking protect sensitive information?

Data masking hides or replaces selected information so that a person or system can work with a less revealing version. A support dashboard might display only the final digits of a telephone number instead of showing the complete value.

Common approaches include:

• Replacing characters with symbols.

• Removing sensitive fields from an exported dataset.

• Showing restricted users a masked view while authorised users retain access to the original.

Google Cloud’s transformation documentation illustrates character masking and other ways to transform sensitive values.

The protection depends on where masking happens. Hiding text visually on a webpage offers little protection if the complete value remains available in the page source or network response.

Masking also needs to cover relevant logs, exports and integrations. Other fields may still identify a person, so masked information should not automatically be treated as anonymous. This distinction is particularly important when configuring session replay privacy controls.