Temporal Pattern in Tweeting Behavior for Persons' Identity Verification

Social interactions via Online Social Network (OSN) can provide a gamut of information about users that have been recently studied as behavioral patterns for person recognition. Similar to social interactions, the temporal information of persons in OSN is likely to exhibit behavioral characteristic and habitual pattern. This paper presents the first empirical study to answer a question whether temporal information obtained via OSN may contain sufficient behavioral biometric properties. In this paper, we present a methodology to identify a set of idiosyncratic temporal features and develop a system based on those unique features for identity verification. To the best of our knowledge, this is the first study on identity verification based on solely temporal profile obtained from an online social network. Experiments demonstrate that the proposed unique temporal profile in OSN can be utilized for users' identity verification, as it obtained low EER of 12% and high AUC of 95.2% in a closed-set test scenario. Potential applications of the proposed temporal profile include identity verification, anomaly and fraud detection, identity theft, continuous authentication, human behavior analysis, and so on.