L-diversity is an extension of the k-anonymity model. While k-anonymity ensures that each individual in a dataset is indistinguishable from at least k-1 others, l-diversity adds another layer by ensuring that for any given set of quasi-identifiers, there are at least l "well-represented" values for the sensitive attribute. This means that even if someone can isolate a group of records, the sensitive information within that group will still be diverse enough to protect individual identities.
