This book is on biometric authentication and proposes to use keystroke dynamics to avoid password-based authentication problems such as shared or stolen. The difficulties concerning password-based are that most users option for simple passwords. They prefer using similar passwords spanning distinct applications (Vance, 2010). Keystroke dynamics is known to overcome these circumstances. Keystroke dynamics measures the rhythms that a person exhibits while typing on a keyboard. In this sense, keystroke dynamics is a behavioural biometric modality, as well as signature dynamics, gait and voice (Klevans and Rodman, 1997; Monrose and Rubin, 2000; Impedovo and Pirlo, 2007; Moustakas et al., 2010). Among the advantages of keystroke dynamics in comparison to other modalities, it can be mentioned here that it is a low-cost modality: indeed, neither extra sensor nor device is required (Giot et al., 2011; Bours, 2012). The counterpart to this low cost and ease of use is the worst performances compared to those obtained with morphological biometric modalities such as fingerprint, face and iris (Wildes, 1997; Maio and Jain, 2009). The rather worse performances of keystroke dynamics (in comparison to other modalities) can be explained by the large intra-class variability of the users’ behaviour. Indeed, the way of typing continuously evolves when time elapses. One way to handle this variability is to consider additional information in the decision process. Future perspectives of these security procedures could be a new paradigm in cybersecurity applications.