k-Anonymity

k-anonymity is one of the classical privacy models developed to reduce re-identification risk. The core idea is that no record should be distinguishable within a very small group when using quasi-identifiers. This is usually achieved through generalization, suppression, or aggregation techniques. However, k-anonymity alone does not solve all privacy risks; additional protections may be needed against homogeneity and background knowledge attacks. Even so, it provides an important starting framework for privacy-preserving data sharing.