Enforcing transparent access to private content in social networks by means of automatic sanitization

TL;DR

This paper introduces an independent, software-based system that automatically detects and sanitizes sensitive content in social media posts, enabling privacy-preserving access tailored to user credentials without depending on social network platforms.

Contribution

It presents a novel, platform-independent scheme for automatic sensitive data detection and sanitization in social networks, enhancing privacy control without requiring platform collaboration.

Findings

System effectively detects sensitive data in user posts

Sanitized content preserves utility while protecting privacy

Applicable to various social platforms with case studies

Abstract

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 information and that external entities can gather and exploit this knowledge for their own benefit. Even though some methods to preserve the privacy of social networks users 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. 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 well-known and already deployed social platforms. 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 data in users' publications; (ii) construct sanitized versions of such data; and (iii) provide privacy-preserving transparent access to sensitive contents by disclosing more or less information to readers according to their credentials toward the owner of the publications. We also study the applicability of the proposed system in general and illustrate its behavior in two case studies.