Title :
Privacy-Preserving Enhanced Collaborative Tagging
Author :
Parra-Arnau, Javier ; Perego, Andrea ; Ferrari, Elena ; Forne, Jordi ; Rebollo-Monedero, David
Author_Institution :
Dept. of Telematics Eng., Univ. Polite`cnica de Catalunya, Barcelona, Spain
Abstract :
Collaborative tagging is one of the most popular services available online, and it allows end user to loosely classify either online or offline resources based on their feedback, expressed in the form of free-text labels (i.e., tags). Although tags may not be per se sensitive information, the wide use of collaborative tagging services increases the risk of cross referencing, thereby seriously compromising user privacy. In this paper, we make a first contribution toward the development of a privacy-preserving collaborative tagging service, by showing how a specific privacy-enhancing technology, namely tag suppression, can be used to protect end-user privacy. Moreover, we analyze how our approach can affect the effectiveness of a policy-based collaborative tagging system that supports enhanced web access functionalities, like content filtering and discovery, based on preferences specified by end users.
Keywords :
data privacy; social networking (online); Web access functionalities; collaborative tagging services; content discovery; content filtering; cross referencing; end-user privacy protection; free-text labels; offline resources; online resources; policy-based collaborative tagging system; privacy-enhancing technology; privacy-preserving collaborative tagging service; social bookmarking; tag suppression; Collaboration; Data privacy; Entropy; Privacy; Semantics; Tag clouds; Policy-based collaborative tagging; Shannon´s entropy; privacy-enhancing technology; privacy-utility tradeoff; social bookmarking; tag suppression;
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
DOI :
10.1109/TKDE.2012.248