Typing Rhythm Research Articles

A systematic review on keystroke dynamics

Abstract Computing and communication systems have improved our way of life, but have also contributed to an increased data exposure and, consequently, to identity theft. A possible way to overcome this issue is by the use of biometric technologies for user authentication. Among the possible technologies to be analysed, this work focuses on keystroke dynamics, which attempts to recognize users by their typing rhythm. In order to guide future researches in this area, a systematic review on keystroke dynamics was conducted and presented here. The systematic review method adopts a rigorous procedure with the definition of a formal review protocol. Systematic reviews are not commonly used in artificial intelligence, and this work contributes to its use in the area. This paper discusses the process involved in the review along with the results obtained in order to identify the state of the art of keystroke dynamics. We summarized main classifiers, performance measures, extracted features and benchmark datasets used in the area.

Capturing Cognitive Fingerprints from Keystroke Dynamics

Conventional authentication systems identify a user only at the entry point. Keystroke dynamics can continuously authenticate users by their typing rhythms without extra devices. This article presents a new feature called cognitive typing rhythm (CTR) to continuously verify the identities of computer users. Two machine techniques, SVM and KRR, have been developed for the system. The best results from experiments conducted with 1,977 users show a false-rejection rate of 0.7 percent and a false-acceptance rate of 5.5 percent. CTR therefore constitutes a cognitive fingerprint for continuous. Its effectiveness has been verified through a large-scale dataset. This article is part of a special issue on security.

S121012 タイピング駆動型身体的引き込みキャラクタを用いた多人数チャットシステム([S121-01]ヒューマンインタフェース(1))

In recent years, character chat is widely used as a means of communication in remote areas. In particular, character chat is used by people around the world in online games, etc. In face-to-face communication, humans share embodied rhythms, that is, the listener's movements such as nodding and body movements, are synchronized with the speaker's speech. This phenomenon, called entrainment, plays an important role in smooth interaction and communication. We have developed an embodied entrainment technology called iRT(InterRobot Technology) that generates automatically communicative movements based on voice input. In order to support communication via virtual characters in an online chat, we applied iRT to the characters and developed a typing-driven embodied entrainment character chat system "InterChat" that generates a character's interactive movements from the user's typing rhythms and natural movements from the meaning of messages in transmission and reception. In this paper, in consideration of the practical use for multiple users, we propose an arrangement of characters in chat system for four users, and we conduct the chat communication experiment. In addition, based on the evaluation result, we develop a typing-driven embodied entrainment character chat system for up to six users.

Comparison of Feature Vectors in Keystroke Dynamics

A number of current applications require algorithms able to extract a model from one-class data and classify unseen data as self or non-self in a novelty detection scenario, such as spam identification and intrusion detection. In this paper the authors focus on keystroke dynamics, which analyses the user typing rhythm to improve the reliability of user authentication process. However, several different features may be extracted from the typing data, making it difficult to define the feature vector. This problem is even more critical in a novelty detection scenario, when data from the negative class is not available. Based on a keystroke dynamics review, this work evaluated the most used features and evaluated which ones are more significant to differentiate a user from another using keystroke dynamics. In order to perform this evaluation, the authors tested the impact on two benchmark databases applying bio-inspired algorithms based on neural networks and artificial immune systems.

Investigating & Improving The Reliability And Repeatability Of Keystorke Dynamics Timers

One of the most challenging tasks facing the security expert remains the correct authentication of human being which has been crucial to the fabric of our society. The emphasis is now on reliable person identification for computerized devices as the latter forms an integral part of our daily activities. Moreover with increasing geographical mobility of individuals, the identification problem has become more acute. One alternative, to curb down the increasing number of computer related crimes, is through the use of keystroke biometric technology which represents an enhancement to password mechanisms by incorporating typing rhythms in it. Time captured being critical to the performance of the identifier, it is primordial that it satisfies certain requirements at a suitable degree of acceptability This paper presents an evaluation of timing options for keystroke dynamics paying attention to their repeatability and reliability as well as their portability on different systems. In actual passwords schemes users enroll using one computer and access resources using other configurations at different locations without bothering about the different underlying operating systems.

2211 InterChat : タイピング駆動型身体引き込みキャラクタチャットシステム(OS10-2 ヒューマンインタフェース・ユーザビリティII)

InterActor is a CG-embodied interaction character driven by iRT which is the InterRobot Technology that enables communicative motions and actions based on only speech input for entrained interaction and communication. In this paper, an embodied entrainment character chat system "InterChat" is developed by introducing an enhanced iRT model that can create motions where the communicative motions and natural actions can be generated easily from both the typing rhythms and the meaning of the words of sending and receiving messages because the typing rhythms resemble the speech rhythms. The effectiveness of this system for chat communication support is demonstrated by a sensory evaluation experiment conducted in a chat communication. As a result, this system is expected to be the basis for a new type of interactive chat communication.

Keystroke analysis of free text

Keystroke dynamics can be useful to ascertain personal identity even after an authentication phase has been passed, provided that we are able to deal with the typing rhythms of free text, chosen and entered by users without any specific constraint. In this paper we present a method to compare typing samples of free text that can be used to verify personal identity. We have tested our technique with a wide set of experiments on 205 individuals, obtaining a False Alarm Rate of less than 5% and an Impostor Pass Rate of less than 0.005%. Different trade-offs are, however, possible. Our approach can rely on what is typed by people because of their normal job, and a few lines of text, even collected in different working sessions, are sufficient to reach a high level of accuracy, which improves proportionally to the amount of available information: As a consequence, we argue that our method can be useful in computer security as a complementary or alternative way to user authentication and as an aid to intrusion detection.

Identity verification through dynamic keystroke analysis

Typing rhythms are the rawest form of data stemming from the interaction between users and computers. When properly sampled and analyzed, they may become a useful tool to ascertain personal identity. Moreover, unlike other biometric features, typing dynamics have an important characteristic: they still exist and are available even after an access control phase has been passed. As a consequence, keystroke analysis can be used as a viable tool for user authentication throughout the work session. In this paper we present an original approach to identity verification based on the analysis of the typing rhythms of individuals on different texts. Our experiments involve 130 volunteers and reach the best outcomes found in the literature, using a smaller amount of information than in other works, and avoiding any form of tailoring of the system to the available data set. The method described in the paper is easily tuned to reach an acceptable trade-off between the need to spot most impostors and to avoid false alarms, and, as a consequence, it can become a valid aid to intrusion detection.