keystroke dynamics

击键动力学
  • 文章类型: Journal Article
    数字技术能否提供一种被动的不显眼的手段来观察和研究实验室之外的认知?以前,认知评估和监测在实验室或临床环境中进行,允许认知状态的横截面一瞥。在过去的十年里,研究人员一直在利用技术进步和设备来探索评估现实世界中认知的方法。我们建议智能手机的虚拟键盘,一个越来越普遍的数字设备,可以为被动数据收集提供理想的渠道来研究认知。被动数据收集在没有参与者积极参与的情况下发生,并允许近乎连续的,客观数据收集。最重要的是,这种数据收集可以发生在现实世界中,捕获真实的数据点。这种数据收集方法及其分析提供了对认知状态的更全面和潜在更合适的见解,随着时间的推移,个体内部的认知波动已被证明是认知能力下降的早期表现。我们回顾被动数据的不同方式,以击键动力学为中心,从智能手机收集,已用于评估和评估认知。我们还讨论了文献中的差距,在这些差距中,利用被动数据的未来方向可以继续为认知提供推论,并阐述数字数据隐私和同意的重要性。
    Can digital technologies provide a passive unobtrusive means to observe and study cognition outside of the laboratory? Previously, cognitive assessments and monitoring were conducted in a laboratory or clinical setting, allowing for a cross-sectional glimpse of cognitive states. In the last decade, researchers have been utilizing technological advances and devices to explore ways of assessing cognition in the real world. We propose that the virtual keyboard of smartphones, an increasingly ubiquitous digital device, can provide the ideal conduit for passive data collection to study cognition. Passive data collection occurs without the active engagement of a participant and allows for near-continuous, objective data collection. Most importantly, this data collection can occur in the real world, capturing authentic datapoints. This method of data collection and its analyses provide a more comprehensive and potentially more suitable insight into cognitive states, as intra-individual cognitive fluctuations over time have shown to be an early manifestation of cognitive decline. We review different ways passive data, centered around keystroke dynamics, collected from smartphones, have been used to assess and evaluate cognition. We also discuss gaps in the literature where future directions of utilizing passive data can continue to provide inferences into cognition and elaborate on the importance of digital data privacy and consent.
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  • 文章类型: Journal Article
    身份验证是在数字应用程序中对用户的个人信息保密的过程。此外,数字平台中的用户认证过程通过生物识别等一些认证方法来验证自己的用户,语音识别,等等。传统上,使用基于一次性登录的凭据验证方法进行用户身份验证。最近,提出了几种新的方法来增强用户身份验证框架,但是在身份验证执行过程中发现这些方法不一致。因此,这篇评论文章的主要动机是分析语音识别等认证系统的优缺点,击键,和小鼠动力学。在连续的非用户身份验证环境中对这些身份验证模型进行评估,并以表格和图形表示的方式呈现了它们的结果。此外,讨论部分广泛解释了所讨论的身份验证系统的共同优缺点。从今以后,这项研究将帮助研究人员在每个阶段采用最合适的方法来构建非侵入式主动认证的认证框架。
    Authentication is the process of keeping the user\'s personal information as confidential in digital applications. Moreover, the user authentication process in the digital platform is employed to verify the own users by some authentication methods like biometrics, voice recognition, and so on. Traditionally, a one-time login based credential verification method was utilized for user authentication. Recently, several new approaches were proposed to enhance the user authentication framework but those approaches have been found inconsistent during the authentication execution process. Hence, the main motive of this review article is to analyze the advantage and disadvantages of authentication systems such as voice recognition, keystroke, and mouse dynamics. These authentication models are evaluated in a continuous non-user authentication environment and their results have been presented in way of tabular and graphical representation. Also, the common merits and demerits of the discussed authentication systems are broadly explained discussion section. Henceforth, this study will help the researchers to adopt the best suitable method at each stage to build an authentication framework for non-intrusive active authentication.
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