What is the difference between Data Masking and Tokenization, and where would you appropriately use each?

Data masking and tokenization are both data security techniques used to protect sensitive data, but they work differently and are appropriate for different use cases. Data masking, also known as data obfuscation, involves replacing sensitive data with modified or fabricated data. The masked data retains the same format and characteristics as the original data but is no longer authentic. This allows users to work with the masked data without exposing the actual sensitive information. Data masking techniques include: Substitution: Replacing sensitive data with other values from a lookup table or a predefined set of values. Shuffling: Rearranging the order of data elements within a field. Redaction: Removing or obscuring parts of the data, such as replacing characters with asterisks. Encryption: Encrypting the data using a reversible encryption algorithm. Data masking is typically used in non-production environments, such as development, testing, and training, where real data is not required but realistic data is needed for testing and development purposes. Tokenization, on the other hand, involves replacing sensitive data with a non-sensitive placeholder called a token. The token is a randomly generated value that has no intrinsic meaning or relationship to the original data. The token is stored separately from the sensitive data in a secure token vault. When an application needs to access the sensitive data, it presents the token to the tokenization system, which retrieves the original data from the vault and provides it to the application. Tokenization is typically used in production environments, such as e-commerce websites and payment processing systems, where sensitive data needs to be protected but still accessible to authorized applications. Tokenization is particularly useful for protecting payment card data, as it allows merchants to process payments without storing the actual card numbers on their systems, reducing the risk of data breaches and PCI compliance requirements. The key differences between data masking and tokenization are: Data masking modifies the data, while tokenization replaces the data. Data masking retains the format and characteristics of the original data, while tokenization does not. Data masking is typically used in non-production environments, while tokenization is typically used in production environments. Data masking is less secure than tokenization, as the masked data may still be vulnerable to reverse engineering or data leakage. Tokenization is more secure than data masking, as the tokens have no intrinsic value and cannot be used to derive the original data. In summary, data masking is suitable for situations where realistic but non-sensitive data is needed, while tokenization is appropriate for situations where sensitive data needs to be protected but still accessible to authorized applications.