What's pseudonymization? Definition, benefits, comparisons
Blog post from Basis Theory
Pseudonymization is a reversible de-identification method that replaces personally identifiable information with aliases, masks, random values, hashes, or format-preserving substitutes while retaining a protected mapping that can restore an individual’s identity when necessary. Unlike anonymization, which aims to make re-identification impossible by eliminating both direct identifiers and potentially identifying combinations such as gender, birth date, and ZIP code, pseudonymization preserves data utility but requires strict protection of lookup tables and related access controls. Organizations use it to reduce hiring bias, secure sensitive systems, limit risks when sharing data with third parties, support GDPR compliance, and create realistic but non-identifiable testing data. In payment environments, it can protect card and bank details, enable safer processing, and support authorized analytics and fraud detection. Tokenization, which substitutes sensitive raw values such as Social Security numbers with newly generated tokens, is presented as a practical way to implement pseudonymization alongside controls for securely processing and sharing data.
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