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In this paper we study the privacy preservation properties of a specific technique for query log anonymization: tokenbased hashing. In this approach, each query is tokenized, and then a secure hash function is applied to each token. We show that statistical techniques may be applied to partially compromise the anonymization. We then analyze the specific risks that arise from these partial compromises, focused on revelation of identity from unambiguous names, addresses, and so forth, and thedoi:10.1145/1242572.1242657 dblp:conf/www/KumarNPT07 fatcat:4qfaggyu3zc3jd5qurzfwpcqqy