K-Anonymity
Last updated
Last updated
K-Anonymity is an early de-identification technique, involving grouping individuals with similar attributes to make them indistinguishable. It has been a trusted method for preserving privacy but is vulnerable to many privacy attacks.
Vulnerable to Re-identification:
K-Anonymity does not address the risk of re-identification. attackers can still identify individuals by combining quasi-identifiers from multiple data sources.
Homogeneity Risk:
Creating homogeneous groups to achieve K-Anonymity may result in a loss of data utility and accuracy of the analysis.
Attribute Disclosure:
Attackers can use external information or background knowledge to infer sensitive attributes from the anonymized data.
Linkage Attacks:
By combining anonymized data with publicly available data or auxiliary information, attackers can re-identify individuals within K-Anonymity groups.
Background Knowledge Attacks:
Attackers can exploit background information to reveal individual identities within K-Anonymity groups.
