A Survey of Keystroke Dynamics Biometrics <s> Data <s> The progress in the field of human-computer interaction with hand held electronic devices, such as, personal digital assistants (PDAs) and mobile phones searches for new interaction techniques. Proximity sensing extends the concept of computer-human interaction beyond actual physical contact with a device. In this paper, a virtual keyboard implementation is presented and keystroke recognition experiments with the keyboard utilizing proximity measurements are described. An infrared (IR) transceiver array is used for detecting the proximity of a finger. Keystroke recognition accuracy is examined with k-nearest neighbor (k-NN) classifier while a multilayer perceptron (MLP) classifier is designed for online implementation. Experiments and results of keystroke classification are presented for both classifiers. The recognition accuracy, which is between 78% and 99% for k-NN classifier and between 69% and 96% for MLP classifier, depends mainly on the location of a specific key on the keyboard area. <s> BIB001 </s> A Survey of Keystroke Dynamics Biometrics <s> Data <s> This paper presents the study to develop and evaluate techniques to authenticate valid users, using the keystroke dynamics of a user's PIN number entry on a numerical keypad, with force sensing resistors. Added with two conventional parameter lists of elements, i.e. digraph latency times and key hold times, keying force was chosen as a third element. Two experiments were conducted. The first experiment was to evaluate whether the three types of elements derived from keystrokes have a significant effect for subjects and to examine how trials and session effects generated the variation of the three elements. The second experiment was to demonstrate the system performance by calculating the False Rejection Rate (FRR) and the False Acceptance Rate (FAR) of the system. In the second experiment, a total of 20 keystrokes were recorded from each subject one week after the memorizing session, in order to evaluate the FRR of the system. To evaluate the FAR of the system, the subjects pretended to be impostors, and ... <s> BIB002 </s> A Survey of Keystroke Dynamics Biometrics <s> Data <s> In everyday life many actions are secured and/or authenticated by use of a secret personal identification number (PIN). This paper reports an improvement to the security afforded by a numeric PIN system through the addition of a covert biometric identification process. This biometric identification process is achieved through the use of a modified keypad incorporating force sensors within the individual keys, these sensors permit the dynamic measurement of applied force and key-press timings, providing an advantage over existing keystroke dynamic techniques which rely on time-domain information only. Details of the experimental setup used are given, and the results from initial tests are reported. In these tests an equal error rate of approximately 10% is obtained and a false acceptance rate of15% with a corresponding false rejection rate of0% has been shown. <s> BIB003 </s> A Survey of Keystroke Dynamics Biometrics <s> Data <s> The purpose of this study is to evaluate the performance of static keystroke analysis as a complimentary and transparent security solution in the context of perimeter defense and facility access. A biometric keypad prototype was developed to evaluate the classification accuracy using temporal keystroke characteristics and feature points extracted from pressure sensors embedded within the keypad. A novel method is proposed to improve keystroke classification accuracy by analyzing 3 pressure related characteristics: amplitude or peak, peak area, and peak sharpness. <s> BIB004 </s> A Survey of Keystroke Dynamics Biometrics <s> Data <s> A new approach for keystroke-based authentication when using a cellular phone keypad as input device is presented. In the proposed method, users are authenticated using keystroke dynamics acquired when typing fixed alphabetic strings on a mobile phone keypad. The employed statistical classifier is able to perform user verification with an average equal error rate of about 13%. The obtained experimental results suggest that, when using mobile devices, a strong secure authentication scheme cannot rely on the sole keystroke dynamics, which however can be a module of a more complex system including, as basic security, a password-based protocol eventually hardened by keystroke analysis. <s> BIB005 </s> A Survey of Keystroke Dynamics Biometrics <s> Data <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> BIB006 </s> A Survey of Keystroke Dynamics Biometrics <s> Data <s> Internet services are important part of daily activities for most of us. These services come with sophisticated authentication requirements which may not be handled by average Internet users. The management of secure passwords for example creates an extra overhead which is often neglected due to usability reasons. Furthermore, password-based approaches are applicable only for initial logins and do not protect against unlocked workstation attacks. In this paper, we provide a non-intrusive identity verification scheme based on behavior biometrics where keystroke dynamics based-on free-text is used continuously for verifying the identity of a user in real-time. We improved existing keystroke dynamics based verification schemes in four aspects. First, we improve the scalability where we use a constant number of users instead of whole user space to verify the identity of target user. Second, we provide an adaptive user model which enables our solution to take the change of user behavior into consideration in verification decision. Next, we identify a new distance measure which enables us to verify identity of a user with shorter text. Fourth, we decrease the number of false results. Our solution is evaluated on a data set which we have collected from users while they were interacting with their mail-boxes during their daily activities. <s> BIB007 </s> A Survey of Keystroke Dynamics Biometrics <s> Data <s> Smartphones are increasingly being used to store personal information as well as to access sensitive data from the Internet and the cloud. Establishment of the identity of a user requesting information from smartphones is a prerequisite for secure systems in such scenarios. In the past, keystroke-based user identification has been successfully deployed on production-level mobile devices to mitigate the risks associated with naive username/password based authentication. However, these approaches have two major limitations: they are not applicable to services where authentication occurs outside the domain of the mobile device--such as web-based services; and they often overly tax the limited computational capabilities of mobile devices. In this paper, we propose a protocol for keystroke dynamics analysis which allows web-based applications to make use of remote attestation and delegated keystroke analysis. The end result is an efficient keystroke-based user identification mechanism that strengthens traditional password protected services while mitigating the risks of user profiling by collaborating malicious web services. We present a prototype implementation of our protocol using the popular Android operating system for smartphones. <s> BIB008
Acquisition. This is the fundamental stage whereby raw keystroke data are collected via various input devices. These may consist of normal computer keyboard [20]  BIB007 , customized pressure sensitive keyboard   , virtual keyboard BIB001 , special purpose num-pad BIB002 BIB003 BIB004 , cellular phone BIB005 BIB006 , and smart phone BIB008 .