Enforcing Transparent Access to Private Content in Social Networks by Means of Automatic Sanitization

Social networks have become an essential meeting point for millions of individuals willing to publish and consume huge quantities of heterogeneous information. Some studies have shown that the data published in these platforms may contain sensitive personal data and that external entities can gather and exploit this knowledge for their own benefit. Even though some methods to preserve the privacy of the users of social networks have been proposed, they generally apply rigid access control measures to the protected content and, even worse, they do not enable the users to understand which contents are sensitive enough to require protection. Last but not least, most of them require the collaboration of social network operators or they fail to provide a practical solution capable of working with wellknown and already deployed social platforms (e.g., Twitter). In this paper, we propose a new scheme that addresses all these issues. The new system is envisaged as an independent piece of software that does not depend on the social network in use and that can be transparently applied to most existing ones. According to a set of privacy requirements intuitively defined by the users of a social network, the proposed scheme is able to: (i) automatically detect sensitive information in users’ publications; (ii) construct sanitized versions of such data; and (iii) provide transparent access to private contents and disclose more or less information (thus, achieving less or more privacy) to readers according to their credentials toward the owners of the publications. We also study the applicability of the proposed system in general and illustrate its behavior in two well-known social networks (i.e., Twitter and PatientsLikeMe).