Which of the following is a method of anonymizing data?

Tokenization is a method of anonymizing data by replacing sensitive data elements with non-sensitive equivalents, referred to as tokens. These tokens can be used in place of the original data for processing or storage purposes, thereby minimizing exposure to sensitive information. The original data is stored securely in a separate location, allowing for data retrieval when needed, but ensuring that the sensitive information is not directly accessible during normal operations.

This method is particularly effective in protecting data such as credit card numbers or personal identification information. Since tokenization allows for the original data to be referenced only under secure conditions, it provides a strong layer of privacy and security, critical for compliance with regulations like PCI DSS and GDPR.

Other methods mentioned, such as data masking or data scrubbing, serve different purposes and may not fully anonymize data in the same way tokenization does. Data masking obfuscates data for non-secure access, while data scrubbing is about cleaning data sets by removing inaccuracies or obsolete records. Aggregation and banding involve grouping data in ways that obscure individual data points, but these approaches do not provide the same level of protection as tokenization, which directly replaces sensitive information with non-sensitive tokens.