ComputingComputer ScienceInformation TechnologyCryptographyInformation RetrievalPrivacy EngineeringData AnonymizationData ProtectionData SecurityPrivacy-preserving AnalyticsQuery ProcessingSearch Log AnalysisAnonymization AlgorithmsPrivacyQuery Log AnalysisReal-time ProcessingSearch Engine Query LogsSearch Log AnonymizationSearch Query LogsThreshold Cryptography Implementation
The recent release of the American Online (AOL) Query Logs highlighted the remarkable amount of private and identifying information that users are willing to reveal to a search engine. The release of these types of log files therefore represents a significant liability and compromise of user privacy. However, without such data the academic community greatly suffers in their ability to conduct research on real search engines. This paper proposes two specific solutions (rather than an overly general framework) that attempts to balance the needs of certain types of research while individual privacy. The first solution, based on a threshold cryptography system, eliminates highly identifying queries, in real time, without preserving history or statistics about previous behavior. The second solution attempts to deal with sets of queries, that when taken in aggregate, are overly identifying. Both are novel and represent additional options for data anonymization.
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