Challenges in mining social network data

A family of attacks such that even from a single anonymized copy of a social network, it is possible for an adversary to learn whether edges exist or not between specific targeted pairs of nodes is described, suggesting that anonymization contains pitfalls even in very simple settings.

Abstract

The profileration of rich social media, on-line communities, and collectively produced knowledge resources has accelerated the convergence of technological and social networks, producing environments that reflect both the architecture of the underlying information systems and the social structure on their members. In studying the consequences of these developments, we are faced with the opportunity to analyze social network data at unprecedented levels of scale and temporal resolution; this has led to a growing body of research at the intersection of the computing and social sciences.