LAUSR

When we meet a new person, we start by introducing ourselves. We share our names, and other information about our jobs, cities, family status, and so on. This is how socializing and social interactions can start: we first need to identify each other. Identification is a cornerstone in establishing social contacts. We identify ourselves and others by a set of civil (e.g., name, nationality, ID number, gender) and social (e.g., music taste, hobbies, religion) characteristics. This seamlessly carried out identification process in face‐to‐face interactions is challenged in the virtual realms of socializing, such as in online social network (OSN) platforms. New identities (i.e., online profiles) could be created without being subject to any level of verification, making it easy to create fake information and forge fake identities. This has led to a massive proliferation of accounts that represent fake identities (i.e., not mapping to physically existing entities), and that poison the online socializing environment with fake information and malicious behavior (e.g., child abuse, information stealing). Within this milieu, users in OSNs are left unarmed against the challenging task of identifying the real person behind the screen. OSN providers and research bodies have dedicated considerable effort to the study of the behavior and features of fake OSN identities, trying to find ways to detect them. Some other research initiatives have explored possible techniques to enable identity validation in OSNs. Both kinds of approach rely on extracting knowledge from the OSN, and exploiting it to achieve identification management in their realms. We provide a review of the most prominent works in the literature. We define the problem, provide a taxonomy of related attacks, and discuss the available solutions and approaches for knowledge‐based identity management in OSNs.