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Understanding users' keystroke patterns for computer access security

机译:了解用户的击键模式以确保计算机访问安全

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User authentication is a major problem in gaining access rights for computer resources. A recent approach to enhance the computer access rights is the use of biomctric properties as the keystroke rhythms of users. Therefore user authentication for computers can be more secure using keystroke rhythms as biometric authentication. Methods like minimum distance, statistical, vector based, neural network type and data mining techniques have been applied in analyzing the keystroke patterns. In this paper, a vector based algorithm for a recent approach has been applied in the identification of keystroke patterns. Keystroke Identification system that is a neuro physical characteristic is studied to realize biometric authentication.
机译:用户身份验证是获得计算机资源访问权限的主要问题。增强计算机访问权限的最新方法是使用生物特征作为用户的击键节奏。因此,使用键盘节奏作为生物特征认证可以更安全地进行计算机的用户认证。最小距离,统计,基于矢量,神经网络类型和数据挖掘技术等方法已用于分析击键模式。在本文中,一种用于最近方法的基于矢量的算法已被应用于击键模式的识别。研究了一种具有神经物理特性的击键识别系统,以实现生物特征认证。

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