nameobfuscation

Name obfuscation is a process used to conceal or replace real names in text or datasets to prevent the identification of individuals. It is employed to protect privacy, comply with data protection regulations, and enable the sharing of information while reducing exposure of personal identifiers. Name obfuscation focuses on personal identifiers rather than all sensitive data, and its effectiveness depends on the context and the methods used.

Common techniques include redaction (removing names entirely), pseudonymization (replacing names with consistent artificial identifiers, such as John Smith becoming Person_A), tokenization (substituting names with tokens that map to a separate table), masking (replacing characters with symbols or asterisks), and hashing (applying a cryptographic hash to a name). Reversible methods, such as pseudonymization and tokenization with a lookup table, allow re-identification under controlled conditions; irreversible methods, like masking or hashing without access to the original mapping, prevent re-identification. The choice of method depends on the required balance between data utility, auditability, and risk tolerance, and it is important to preserve referential integrity so that cross-record references remain consistent.

Privacy and ethical considerations include reducing re-identification risk and ensuring compliance with laws, while recognizing potential drawbacks such as reduced data utility and the possibility of indirect disclosure through auxiliary information. Best practices involve clearly defining objectives, selecting an appropriate method, documenting the process, restricting access to de-obfuscated data, conducting risk assessments, and testing the impact on data quality and analytical usefulness. Example: replacing a name like Alice Smith with a deterministic pseudonym such as Pseudonym_001 in a research dataset.