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On content-based recommendation and user privacy in social-tagging systems
Puglisi, Silvia; Parra-Arnau, Javier; Forné Muñoz, Jorge; Rebollo Monedero, David
Universitat Politècnica de Catalunya. Departament d'Enginyeria Telemàtica; Universitat Politècnica de Catalunya. ISG - Grup de Seguretat de la Informació
Recommendation systems and content filtering approaches based on annotations and ratings, essentially rely on users expressing their preferences and interests through their actions, in order to provide personalised content. This activity, in which users engage collectively has been named social tagging, and it is one of the most popular in which users engage online, and although it has opened new possibilities for application interoperability on the semantic web, it is also posing new privacy threats. It, in fact, consists of describing online or offline resources by using free-text labels (i.e. tags), therefore exposing the user profile and activity to privacy attacks. Users, as a result, may wish to adopt a privacy-enhancing strategy in order not to reveal their interests completely. Tag forgery is a privacy enhancing technology consisting of generating tags for categories or resources that do not reflect the user's actual preferences. By modifying their profile, tag forgery may have a negative impact on the quality of the recommendation system, thus protecting user privacy to a certain extent but at the expenses of utility loss. The impact of tag forgery on content-based recommendation is, therefore, investigated in a real-world application scenario where different forgery strategies are evaluated, and the consequent loss in utility is measured and compared.
Peer Reviewed
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors::Internet
Computer security
Online social networks
Information Privacy
Privacy-enhancing technology
Privacy Risk
Recommendation system
Social Web
Collaborative tagging
Tag forgery.
Seguretat informàtica
Xarxes socials en línia

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