In this work we inspect different data sources for browser fingerprints. We show which disadvantages and limitations browser statistics have and how this can be avoided with other data sources. Since human visual behavior is a rich source of information and also contains person specific information, it is a valuable source for browser fingerprints. However, human gaze acquisition in the browser also has disadvantages, such as inaccuracies via webcam and the restriction that the user must first allow access to the camera. However, it is also known that the mouse movements and the human gaze correlate and therefore, the mouse movements can be used instead of the gaze signal. In our evaluation we show the influence of all possible combinations of the three information sources for user recognition and describe our simple approach in detail. The data and the Matlab code can be downloaded here https://atreus.informatik.uni-tuebingen.de/seafile/d/8e2ab8c3fdd444e1a135/?p=%2FThe%20Gaze%20and%20Mouse%20Signal%20as%20additional%20Source%20...&mode=list
翻译：在这项工作中,我们检查浏览器指纹的不同数据源。 我们为浏览器指纹检查不同的数据源。 我们显示鼠标运动的缺点和限制浏览器统计, 以及如何与其他数据源避免。 由于人类视觉行为是丰富的信息来源, 并且包含个人特有的信息, 人类视觉行为是浏览器指纹的宝贵来源。 然而, 在浏览器中获取人的凝视也存在缺点, 例如通过网络摄像头获取的不准确性, 以及用户必须首先允许访问相机的限制。 但是, 人们也知道鼠标运动和人类凝视的关联性, 因此, 可以使用鼠标运动来代替凝视信号。 在我们的评估中, 我们展示了三种信息来源的所有可能的组合对用户识别和描述简单方法的影响。 数据和Matlab 代码可以在此下载 https://atreus. informatik. uni-tuebingen.de/seafile/d/8e2aba8c3fd44e1a135? p\2FThe20Gaze% 20and% 20Mouse%20Signal%202020adfistrational%20&modelist=list
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