#anonymization
#anonymization

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Privacy-Preserving Data Publishing: k-Anonymity, t-Plausibility, and More | HackerNoon

Privacy models like k-anonymity are essential for ensuring safe data sharing in NLP while preserving individual privacy.

Linking private and public genetic data poses risks to research participants' health information privacy.

Single-cell data sets are not as secure as previously thought against privacy leaks.

Privacy professionals

Hashing data does not anonymize it; hashed identifiers are considered personal information by regulators like the FTC.

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