A Survey of Keystroke Dynamics Biometrics <s> Timing Resolution. <s> The keystroke dynamics of a computer user's login string provide a characteristic pattern that can be used for identity verification. Timing vectors for several hundred login attempts were collected for ten "valid" users and ten "forgers", and classification analysis was applied to discriminate between them. Three different classifiers were applied, and in each case the key hold times were more effective features for discrimination than the interkey times. Best performance was achieved by an inductive learning classifier using both interkey and hold times. A high rate of typographical errors during login entry is reported. In practice, these are usually corrected errors-that is, they are strings which include backspaces to correct earlier errors-but their presence confounds the use of typing-style analysis as a practical means of securing access to computer systems. <s> BIB001 </s> A Survey of Keystroke Dynamics Biometrics <s> Timing Resolution. <s> Unlike other access control systems based on biometric features, keystroke analysis has not led to techniques providing an acceptable level of accuracy. The reason is probably the intrinsic variability of typing dynamics, versus other---very stable---biometric characteristics, such as face or fingerprint patterns. In this paper we present an original measure for keystroke dynamics that limits the instability of this biometric feature. We have tested our approach on 154 individuals, achieving a False Alarm Rate of about 4p and an Impostor Pass Rate of less than 0.01p. This performance is reached using the same sampling text for all the individuals, allowing typing errors, without any specific tailoring of the authentication system with respect to the available set of typing samples and users, and collecting the samples over a 28.8-Kbaud remote modem connection. <s> BIB002 </s> A Survey of Keystroke Dynamics Biometrics <s> Timing Resolution. <s> Current keystroke dynamics applications have tackled the problem of traditional knowledge-based static password verification, but the problem of spontaneous password verification persists. The intent of this study was to examine the predictive strength of typing patterns for spontaneous passwords. The typing patterns of an individual typing at a DELLreg keyboard on a DELL OptiPlexreg GX260 machine were recorded. Variables collected included keystroke press time and keystroke latency. Computed performance measures included false match rates (FMR) and false non match rates (FNMR) at various threshold levels <s> BIB003 </s> A Survey of Keystroke Dynamics Biometrics <s> Timing Resolution. <s> Keystroke dynamics is a behavioral biometric that is based on how a user enters their login details. In this study, a set of eight attributes were extracted during the course of entering login details. This collection of attributes was used to form a reference signature (a biometrics identification record) for subsequent authentication requests. The algorithm for the authentication step entails transforming the attributes into a discretised form based on the amino acid alphabet. A set of bioinformatics based algorithms are then used to perform the actual authentication test. In addition, the use of rough sets was employed in this study to determine if subsets of attributes were more important in the classification (authentication) than others. Lastly, the results of this study indicate that the error rate is less than 1% in the majority of the cases. <s> BIB004 </s> A Survey of Keystroke Dynamics Biometrics <s> Timing Resolution. <s> The keystroke patterns produced during typing have been shown to be unique biometric signatures. Therefore, these patterns can be used as digital signatures to verify the identity of computer users remotely over the Internet or locally at a specific workstation. In particular, keystroke recognition can enhance the username and password security model by monitoring the way that these strings are typed. To this end, this paper proposes a novel up--up keystroke latency (UUKL) feature and compares its performance with existing features using a Gaussian mixture model (GMM)-based verification system that utilizes an adaptive and user-specific threshold based on the leave-one-out method (LOOM). The results show that the UUKL feature significantly outperforms the commonly used key hold-down time (KD) and down--down keystroke latency (DDKL) features. Overall, the inclusion of the UUKL feature led to an equal error rate (EER) of 4.4% based on a database of 41 users, which is a 2.1% improvement as compared to the existing features. Comprehensive results are also presented for a two-stage authentication system that has shown significant benefits. Lastly, due to many inconsistencies in previous works, a formal keystroke protocol is recommended that consolidates a number of parameters concerning how to improve performance, reliability, and accuracy of keystroke-recognition systems. <s> BIB005 </s> A Survey of Keystroke Dynamics Biometrics <s> Timing Resolution. <s> This paper describes a novel technique to strengthen password authentication system by incorporating multiple keystroke dynamic information under a fusion framework. We capitalize four types of latency as keystroke feature and two methods to calculate the similarity scores between the two given latency. A two layer fusion approach is proposed to enhance the overall performance of the system to achieve near 1.401% Equal Error Rate (EER). We also introduce two additional modules to increase the flexibility of the proposed system. These modules aim to accommodate exceptional cases, for instance, when a legitimate user is unable to provide his or her normal typing pattern due to reasons such as hand injury. <s> BIB006 </s> A Survey of Keystroke Dynamics Biometrics <s> Timing Resolution. <s> Keystroke dynamics is the process of identifying individual users on the basis of their typing rhythms, which are in turn derived from the timestamps of key-press and key-release events in the keyboard. Many researchers have explored this domain, with mixed results, but few have examined the relatively impoverished territory of digits only, particularly when restricted to using a single finger - which might come into play on an automated teller machine, a mobile phone, a digital telephone dial, or a digital electronic security keypad at a building entrance. In this work, 28 users typed the same 10-digit number, using only the right-hand index finger. Employing statistical machine-learning techniques (random forest), we achieved an unweighted correct-detection rate of 99.97% with a corresponding false-alarm rate of 1.51%, using practiced 2-of-3 encore typing with outlier handling. This level of accuracy approaches sufficiency for two-factor authentication for passwords or PIN numbers. <s> BIB007
One of the major factors that contribute to system performance is timing resolution, and thus suitable timing resolution is important so that the keystroke timing vector generated can characterize user typing cadence in the right precision. Earlier research work was implemented at a timing resolution of 10 ms BIB002  , unfortunately detector performance could be limited by the use of such low resolution clock  . However, due to computer processing capacity at that point of time, this was the best precision achievable. Today, high performance computer can reach a clock resolution of micro or even nanoseconds easily. Although greater timing resolution is able to increase performance  , precision as high as nanoseconds is not necessary since no one can achieve such a fast typing speed. Ever since, the most widely used resolution was in the range of 0.1 BIB006 BIB007 BIB001 ] to 1 ms  BIB004 BIB003 . It was recommended by BIB005 that a resolution of at least 1 ms should be used to capture keystroke events. Reference  was dedicated on discussing the relation of clock resolution and the performance of keystroke dynamics detectors. The authors evaluated three established detectors against different clock resolution precisions. Experimental result showed that there is performance improvement, albeit small, by using high-resolution clock as compared to lower ones.