Insider threats are a growing concern for countless organizations worldwide. The main challenge in dealing with insider threats is that insiders are authorized users with legitimate access to sensitive information. An insider threat reaches from within an institution and constitutes a significant security risk. Frequently occurs, insider threats when a trusted employee (current or past) misuses the privileges granted for an illegal purpose. As a result, this study focuses on detecting abnormal behavior using three supervised algorithms to detect insider threats.