Final answer:
Hanna should use data masking to protect sensitive data elements in a dataset used for app testing. Data masking maintains the data format and usefulness for development while preventing exposure of sensitive information.
Step-by-step explanation:
To ensure that sensitive elements of a data set are not exposed while testing a new app, Hanna should use data masking. Data masking, also known as data obfuscation, is the process of hiding original data with modified content (characters or other data). This technique is used to protect sensitive information while still providing a functional dataset for testing or development purposes. Unlike tokenization, which replaces sensitive data with non-sensitive substitutes called tokens, data masking maintains the format of the data and ensures that it is no longer sensitive or identifiable.
Masking techniques can include shuffling, substitution, and anonymization, which keep the data useful for tasks like app testing but do not reveal the actual sensitive data. Selecting the right technique depends on the specific requirements and context of the project at hand. However, data masking is a widely accepted practice for protecting sensitive data in non-production environments.