RT journal article
T1 Privacy protection of user profiles in online search via semantic randomization
A1 Rodríguez García, María Mercedes
A1 Batet, Montserrat
A1 Sánchez, David
A1 Viejo, Alexandre
A2 Ingeniería en AutomáticaElectrónica, Arquitectura y Redes de Computadores
K1 Privacy
K1 Profiling
K1 Query logs
K1 Semantics
AB Querying a search engine is one of the most frequent activities performed by Internet users. As queries are submitted, the server collects and aggregates them to build detailed user profiles. While user profiles are used to offer personalized search services, they may also be employed in behavioral targeting or, even worse, be transferred to third parties. Proactive protection of users' privacy in front of search engines has been tackled by submitting fake queries that aim at distorting the users' real profile. However, most approaches submit either random queries (which do not allow controlling the profile distortion) or queries constructed by following deterministic algorithms (which may be detected by aware search engines). In this paper, we propose a semantically grounded method to generate fake queries that (i) is driven by the privacy requirements of the user, (ii) submits the least number of fake queries needed to fulfill the requirements and (iii) creates queries in a non-deterministic way. Unlike related works, we accurately analyze and exploit the semantics underlying to user queries and their influence in the resulting profile. As a result, our approach offers more control—because users can tailor how their profile should be protected—and greater efficiency—because the desired protection is achieved with fewer fake queries. The experimental results on real query logs illustrate the benefits of our approach.
PB Springer Science and Business Media
SN 0219-1377
YR 2021
FD 2021-07
LK http://hdl.handle.net/10498/38820
UL http://hdl.handle.net/10498/38820
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 21-sep-2026