The correct answer is Obfuscation.

Obfuscation refers to changing or concealing sensitive values so that developers and testers work with realistic looking data while the original secrets remain protected. Typical obfuscation techniques include masking, scrambling, and substitution which preserve data format and usability without exposing real sensitive information in development and testing environments.

Cloud Data Loss Prevention is a vendor service that can detect and deidentify sensitive data and apply transformations, but it is not the generic data protection approach described by the question. The question asks for the approach rather than a specific product.

Anonymization seeks to remove or irreversibly alter identifiers so that individuals cannot be reidentified. That irreversibility often reduces the usefulness of the data for realistic testing and so it does not match the idea of changing values to preserve usability during development.

Tokenization replaces sensitive values with tokens and relies on a secure token vault to map back to the original values. That is a different protection model and it is commonly used in production systems or payment processing rather than as a simple method to provide safe, realistic test data without a vault.

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