Keyword-based approach for recognizing fraudulent messages by keystroke dynamics

•We propose an approach, which combines the techniques of keystroke dynamics, two new prediction methods, a new classifier, and a keyword-based detection mechanism to authenticate US English fraudulent instant messages.•To the best of our knowledge, this study is the first to apply keystroke dynamics to detect fraudulent instant messages.•Experimental results indicate that our proposed approach outperforms other relevant published methods, in terms of shorter training time, less false alarms, and comparable recognition accuracy. In recent years, many approaches that use keystroke dynamics in free text authentication have been proposed. The major drawback of the proposed approaches is that training generally requires several months, thereby resulting in low practicality. In this study, a method to detect U.S. English fraudulent messages by analyzing keyboard users' keystroke dynamics is proposed. To the best of our knowledge, this is the first study to apply keystroke dynamics to detect fraudulent instant messages. In the proposed system, each user requires only approximately 20 min of training in U.S. English keystroke dynamics. Furthermore, a voting-based statistical classifier is presented to improve the recognition accuracy of instant messages and prevent phishing messages. Experimental results indicate that the proposed approach outperforms other relevant published methods in terms of shorter training time, fewer false alarms, and comparable recognition accuracy.