Query log anonymization has become an important challenge nowadays. A query log contains the search history of the users, as well as the selected results and their position in the ranking. These data are used to provide a personalized re-ranking of results and trend studies. However, query logs can disclose sensitive information of the users. Hence, query logs must be submitted to an anonymization process to guarantee that: (a) no sensitive information can be linked to an identity; (b) the analysis of the anonymized data produces similar results than the original data, i.e. minimize data distortion. Latest anonymization approaches utilize microaggregation, a statistical disclosure control technique that provides a privacy comparable with k -anonymity, attempting to minimize the data distortion. We propose a new method that uses search results to optimize microaggregation, providing more data reliability than the existing methods. © 2014 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Erola, A., & Castellà-Roca, J. (2014). Using search results to microaggregate query logs semantically. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8247 LNCS, pp. 148–161). Springer Verlag. https://doi.org/10.1007/978-3-642-54568-9_10
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