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首页> 外文会议>International Conference on Signal Processing, Communication, Power and Embedded System >Multi-phase mouse dynamics authentication system using behavioural biometrics
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Multi-phase mouse dynamics authentication system using behavioural biometrics

机译：使用行为生物识别的多相鼠标动态认证系统

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摘要

In this era, the password-based system is not enough to secure important data. It has, in general, the disadvantage that passwords are either too hard to remember or too easy to guess. It is necessary to apply a higher level of security. This can be achieved by using the biometrics i.e. behavioral biometrics such as using mouse dynamics. In the existing system, the user needs to perform a specified task with his mouse pointer, and based on the performance of that task, the user is granted or denied access to the computer. In this paper, we are proposing a method, where we provide additional mouse dynamics to the existing work i.e. mouse single and double click related tasks and combination of which is later used as their identity. Our intention is to improve the accuracy of the system by adding more features of the mouse for easily classifying the genuine and impostor user. The mouse data obtained from the user is raw data and it has to be normalized and make outlier free to used for the further process so this is resolved by using Peirce's criterion and Weighted Least Square Regression (WLSR) and for classification, we have used Learning Vector Quantization (LVQ).
机译：在这个时代，基于密码的系统不足以确保重要数据。通常，密码要么太难记住或者太容易猜测，它都有缺点。有必要应用更高水平的安全性。这可以通过使用生物识别方法来实现，例如使用鼠标动态的行为生物识别技术。在现有系统中，用户需要用鼠标指针执行指定的任务，并基于该任务的性能，用户被授予或拒绝访问计算机。在本文中，我们正在提出一种方法，在那里我们为现有工作提供额外的鼠标动态即，鼠标单点和双击相关任务，其组合稍后用作它们的身份。我们的目的是通过添加鼠标的更多特征来提高系统的准确性，以便轻松分类真实和冒名顶替者用户。从用户获得的鼠标数据是原始数据，它必须归一化，并且必须对进一步的进程免费进行异常，因此通过使用PeiRCE的标准和加权最小二乘回归（WLSR）和分类来解决这一点，我们已经使用了学习矢量量化（LVQ）。

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