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Identity Verification Using a Kinematic Memory Detection Technique

机译:使用运动存储检测技术的身份验证

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We present a new method that allows the identification of false self-declared identity, based on indirect measures of the memories relating the affirmed personal details. This method exploits kinematic analysis of mouse as implicit measure of deception, while the user is answering to personal information. Results show that using mouse movement analysis, it is possible to reach a high rate of accuracy in detecting the veracity of self-declared identities. In fact, we obtained an average accuracy of 88 % in the classification of single answers as truthful or untruthful, that corresponds overall to 9.7/10 participants correctly classified as true tellers or liars. The advantage of this method is that it does not requires any knowledge about the real identity of the declarant.
机译:我们提出了一种新的方法,允许根据与肯定的个人详细信息相关的记忆的间接测量来确定虚假的自我宣布的身份。此方法利用鼠标的运动分析作为隐含欺骗量度,而用户正在回答个人信息。结果表明,使用鼠标运动分析,可以达到检测自我申报标识的真实性的高精度。事实上,我们在单一答案的分类中获得了88%的平均准确性,作为真实或不真实的,这总体上限为9.7 / 10参与者被正确归类为真正的柜员或骗子。这种方法的优势在于它不需要对申报人的真实身份的任何知识。

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