Institute of Electrical & Electronic Engineers
Online social networks, such as Facebook, are increasingly utilized by many people. These networks allow users to publish details about themselves and connect to their friends. Some of the information revealed inside these networks is meant to be private. Yet it is possible that corporations could use learning algorithms on released data to predict undisclosed private information. In this paper, the authors explore how to launch inference attacks using released social networking data to predict undisclosed private information about individuals.