Utility Preserving Query Log Anonymization via Semantic Microaggregation
Query logs are of great interest for scientists and companies for research, statistical and commercial purposes. However, the availability of query logs for secondary uses raises privacy issues since they allow the identification and/or revelation of sensitive information about individual users. Hence, query anonymization is crucial to avoid identity disclosure. To enable the publication of privacy-preserved but still useful-query logs, in this paper, the authors present an anonymization method based on semantic microaggregation. Their proposal aims at minimizing the disclosure risk of anonymized query logs while retaining their semantics as much as possible.