Semantic microaggregation for the anonymization of query logs using the open directory project
Web search engines gather information from the queries performed by the user in the form of query logs. These logs are extremely useful for research, marketing, or profiling, but at the same time they are a great threat to the user’s privacy. We provide a novel approach to anonymize query logs so th...
| Autores: | , , , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2011 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2099/11415 |
| Acceso en línea: | https://hdl.handle.net/2099/11415 |
| Access Level: | acceso abierto |
| Palabra clave: | Artificial intelligence Privacy Web search engines Query logs K-anonymity Microaggregation Semantic Intel·ligència artificial Classificació AMS::68 Computer science::68T Artificial intelligence Àrees temàtiques de la UPC::Matemàtiques i estadística |
| Sumario: | Web search engines gather information from the queries performed by the user in the form of query logs. These logs are extremely useful for research, marketing, or profiling, but at the same time they are a great threat to the user’s privacy. We provide a novel approach to anonymize query logs so they ensure user k-anonymity, by extending a common method used in statistical disclosure control: microaggregation. Furthermore, our microaggregation approach takes into account the semantics of the queries by relying on the Open Directory Project. We have tested our proposal with real data from AOL query logs |
|---|