Combining Trust Graphs and Keystroke Dynamics to Counter Fake Identities in Social Networks

Fake identity in social networks is a phenomenon that is strongly increasing, and it is used for discovering personal information, identity theft, influencing people, spreading fake news, fraud, and so on. In this paper, we face this problem by introducing the concept of certified social profiles and by propagating this property through a collaborative approach that exploits keystroke-dynamic-recognition techniques to identify illegal access to certified profiles. We propose a decentralized approach to compute the trust level of a social profile, and we show the robustness of the proposal by analyzing the security of the trust mechanism through experimental validation.