De-Anonymizing Users across Rating Datasets via Record Linkage and Quasi-Identifier Attacks

The widespread availability of pseudonymized user datasets has enabled personalized recommendation systems. However, recent studies have shown that users can be de-anonymized by exploiting the uniqueness of their data patterns, raising significant privacy