Due to the amount of personally identifiable information shared by users of online social networks (OSNs) and the often not adequately adjusted privacy settings, it is possible to identify a user's several OSN profiles. In this paper, we illustrate that third parties just have to take a small step to link OSN profiles of a user and, consequently, to aggregate various pieces of information shared in several OSNs. Particularly, based on statistical results we illustrate how the often publicly available friends lists can be exploited to link several OSN profiles of a single natural person. The results presented in this paper show that profiles can be linked even at low cost, i.e., without complex correlation techniques or high computational power. To assess the risk of privacy leakage by profile linking, we, additionally, report how often specific pieces of information are made publicly available by users in four of the most popular OSNs. We show that users tend to publish different pieces of information in different OSNs and, thereby, demonstrate that by linking friends lists more information about a user can be gained than the user s ... mehrhared in a single OSN. For the study we analyzed more than 180,000 user profiles and compared more than seven million pairs of profiles to investigate profile linkability.