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In this chapter we 1) provide a new dataset collected from real-world for researchers to examine possible influence of emotions on user authentication using keystroke dynamics biometrics, or develop their own systems to recognize emotions using keystroke dynamics patterns, 2) summarize recent findings in the field of emotion recognition using keystroke dynamics, and 3) provide concrete suggestions to the field of user authentication using keystroke dynamics biometrics based on the empirical findings derived from the proposed dataset. Emotion plays an essential role in human life because it is the foundation of the moti-vational system of people. Recent studies in the field of psychology, brain science and communication technology have demonstrated the substantial effects of emotion on human cognition and behavior. Lang et al. (1995) reported an empirical study on the effects of emotional characteristics of stimuli on subjects' cognitive capacity and memory [6]. Bolls et al. (2001) revealed the effect that subjects tend to remember stimulus that elicit negative emotions more, than the stimulus that elicit positive emotions [3]. Later researchers focused on the use of emotional relevant stimulus on attracting the attention of subjects and to make subjects remember more on the presented stimuli. Theories and experimental results of the examinations on the connections between emotion and motivation were also reported [7]. Automatic affect recognition technology has been proposed and has attracted considerable attention since its proposal. The proposed technology aims to help in the Human Computer Interaction (HCI) area. This is because a computer interactive application that does not understand or adapt to a user's context, such as their location, professional, or the emotion states of a user, may lead to usability problems. Such an application could provide annoying feedback, interrupt users in an inappropriate situation, or increase the user's frustration. The main purpose of affect recognition technology is to provide intelligent systems that can provide computer applications the information about the changes of human emotions. As a result, the applications equipped with such a technology can detect and respond to a users' emotion state, and could even give a better user experience as well as provide appropriate feedback in helping users in using the applications. Various methods have been proposed to detect emotions, including the use of facial expressions, voice intonation, and physiological signals collected from human body. All of these proposed methods have high classification rate of success. However, the drawback of these methods is that …

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Will User Authentication Using Keystroke Dynamics Biometrics Be Interfered by Emotions? – NCTU-15 Affective Keyboard Typing Dataset for Hypothesis Testing