What is the term for techniques used to protect personally identifiable information (PII) in data sets?

The term that specifically refers to techniques used to protect personally identifiable information (PII) in data sets is "data anonymization." Data anonymization involves altering data so that individuals cannot be readily identified from it. This process is critical for maintaining privacy and security, especially in environments where sensitive data is handled.

Data anonymization techniques can include aggregation, pseudonymization, and other methods that reduce the risk of re-identifying an individual from the data. The main goal is to ensure that even if the data is accessed or breached, it does not compromise personal information. Using data anonymization is essential in compliance with regulations such as the General Data Protection Regulation (GDPR) and the Health Insurance Portability and Accountability Act (HIPAA), which emphasize the protection of PII.

In contrast, the other terms do not specifically describe techniques aimed solely at protecting PII. For example, data privacy pertains more broadly to the governance and overall practices regarding the proper handling of personal information, while data sanitization refers to processes that ensure data is completely and securely deleted or made unrecoverable. PII, on the other hand, simply denotes the actual identifiable information itself rather than the methods of protection.