PrivacySearch: An End-User and Query Generalization Tool for Privacy Enhancement in Web Search
| Autor: | Francisco-Javier Rodrigo-Ginés, Javier Parra-Arnau, Weizhi Meng, Yu Wang |
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| Rok vydání: | 2018 |
| Předmět: |
Service (systems architecture)
User profile Information retrieval Computer science End user Generalization 05 social sciences 02 engineering and technology Transparency (human–computer interaction) Personalized search Search engine Technical feasibility 020204 information systems 0202 electrical engineering electronic engineering information engineering 0509 other social sciences 050904 information & library sciences |
| Zdroj: | Network and System Security ISBN: 9783030027438 NSS |
| DOI: | 10.1007/978-3-030-02744-5_23 |
| Popis: | Web search engines capitalize on, or lend themselves to, the construction of user interest profiles to provide personalized search results. The lack of transparency about what information is stored, how it is used and with whom it is shared, limits the perception of privacy that users have about the search service. In this paper, we investigate a technology that allows users to replace specific queries with more general but semantically similar search terms. Through the generalization of queries, user profile could become less precise and therefore more private, although evidently at the expense of a degradation in the accuracy of search results. In this work, we design and develop a tool of PrivacySearch that implements this principle in real practice. Our tool, developed as a browser plug-in for Google Chrome, enables users to generalize the queries sent to a search engine in an automated fashion, without the need for any kind of infrastructure or external databases, and in real time, according to simple and intuitive privacy criteria. Experimental results demonstrate the technical feasibility and suitability of our solution. |
| Databáze: | OpenAIRE |
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