K-anonymity is a privacy protection technique that ensures each individual data record cannot be distinguished from at least k−1k-1k−1 other records with respect to certain identifying information. This means that each record in the data set is made to look like at least k−1k-1k−1 other records, making it difficult to identify individuals. The primary goal of k-anonymity is to prevent re-identification of individuals in microdata by ensuring that personal records are indistinguishable within a group of size kkk. This concept is widely discussed in IAPP materials related to data de-identification and anonymization (IAPP, "Anonymization and Pseudonymization").
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