Anonymization and pseudonymization guides
Practical guides about personal data, documents, AI and re-identification risk.
Anonymization vs pseudonymizationWhat is data masking?Is removing a name enough?How to prepare text for AI toolsHow to remove personal data from a documentHow to safely redact and anonymize PDF textWhy a black box may not remove PDF textHow to anonymize a Word documentHow to anonymize Excel and CSV dataHow to anonymize research dataHow to anonymize survey responsesHow to anonymize interview transcriptsHow to anonymize health dataHow to anonymize HR documentsHow to anonymize customer support casesHow to anonymize email messagesHow to anonymize server logsHow to remove API keys and tokensHow to mask email addressesHow to mask phone numbersHow to detect national identification numbers safelyHow to mask tax and business IDsHow to mask bank account numbersHow to mask payment card numbers safelyHow to anonymize IP addressesHow to generalize dates of birthHow to generalize location dataWhat are quasi-identifiers?What is k-anonymity?Limitations of k-anonymityNo record isolation, no linkage and no inferenceHow to assess re-identification riskWhy pseudonymized data may still be personal dataHow to protect a pseudonym mapHash or HMAC for pseudonymization?How to create test data without copying customer recordsSynthetic data vs anonymous dataHow to verify an anonymization resultAnonymization vs metadata removalHow local browser processing worksWhat personal data can remain in DOCX comments?Hidden Excel sheets and privacyPresenter notes in PowerPointHow to anonymize SRT and VTT subtitlesAnonymizing JSON without breaking its structureHow to anonymize an SQL dumpHow to create a custom detection ruleCommon anonymization mistakesWhen a professional assessment is neededChecklist before publishing a dataset