A Survey of Keystroke Dynamics Biometrics <s> Artificial Rhythm and <s> Biometrics based user authentication involves collecting user's patterns and then using them to determine if a new pattern is similar enough. The quality of the user's patterns is as important as the quality of the classifier. But, the issue has been ignored in the literature since the popular biometrics are mostly trait based such as finger prints and iris so that its pattern quality depends on the quality of the input device involved. However, the quality of the user's patterns of behavior based biometric such as keystroke dynamics can be improved artificially by increasing the peculiarity of the typing style. In this paper, we propose several ways to improve the quality. But, first we define the quality of patterns in terms of two factors: uniqueness and consistency. Finally, the results of a preliminary experiment are presented that support the utility of the proposed methods. <s> BIB001 </s> A Survey of Keystroke Dynamics Biometrics <s> Artificial Rhythm and <s> Keystroke dynamics based user authentication (KDA) can achieve a relatively high performance if a fairly large number of typing patterns are available. It is almost always the case that KDA is combined with password based authentication. Users are often required to change their passwords. When a user changes one's password, however, only a handful of new patterns become available. In a mobile situation, moreover, very short passwords are used. Under such a circumstance, the quality of data becomes important. Recently, artificial rhythms and cues were proposed to improve the quality of data. In this paper, we verify the effectiveness of artificial rhythms and cues through hypotheses tests using the data from 25 users under various situations. The experimental results show that artificial rhythms increase the uniqueness while cues increase the consistency. <s> BIB002 </s> A Survey of Keystroke Dynamics Biometrics <s> Artificial Rhythm and <s> Keystroke dynamics-based authentication (KDA) is to verify a user's identity using not only the password but also keystroke dynamics. With a small number of patterns available, data quality is of great importance in KDA applications. Recently, the authors have proposed to employ artificial rhythms and tempo cues to improve data quality: consistency and uniqueness of typing patterns. This paper examines whether improvement in uniqueness and consistency translates into improvement in authentication performance in real-world applications. In particular, we build various novelty detectors using typing patterns based on various strategies in which artificial rhythms and/or tempo cues are implemented. We show that artificial rhythms and tempo cues improve authentication accuracies and that they can be applicable in practical authentication systems. <s> BIB003 </s> A Survey of Keystroke Dynamics Biometrics <s> Artificial Rhythm and <s> Recently, mobile devices are used in financial applications such as banking and stock trading. However, unlike desktops and notebook computers, a 4-digit personal identification number (PIN) is often adopted as the only security mechanism for mobile devices. Because of their limited length, PINs are vulnerable to shoulder surfing and systematic trial-and-error attacks. This paper reports the effectiveness of user authentication using keystroke dynamics-based authentication (KDA) on mobile devices. We found that a KDA system can be effective for mobile devices in terms of authentication accuracy. Use of artificial rhythms leads to even better authentication performance. <s> BIB004
Cue. The quality of keystroke dynamics can be improved artificially by increasing the distinctiveness and peculiarity of typing pattern BIB001 , thereby evades the increase of hardware implementation cost. Uniqueness and consistency are the two core factors revealed by BIB002 , which determine quality of keystroke feature. Uniqueness associated with how dissimilar an intruder's input pattern compared to the reference template while consistency implies to what degree a user's typing pattern matches the enrolled template during registration. The author proposed that uniqueness could be enhanced by incorporating artificially designed rhythms during input process such as pauses, musical rhythm, staccato, legato, and slow tempo. Similarly, auditory and visual cues were introduced with the aim of increasing consistency. As a consequence, legitimate users' typing patterns could be better separated from intruders' BIB003 . By having better quality data, the number of enrolment samples required for constructing reliable reference template can be radically reduced BIB004 . Thus, using artificial rhythms and cues has an additional advantage of reducing user's 14 The Scientific World Journal burden in terms of providing repeated samples during registration stage.