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Using Medical History Embedded in Biometrics Medical Card for User Identity Authentication: Privacy Preserving Authentication Model by Features Matching

机译:使用生物识别医疗卡中嵌入的病历进行用户身份验证:通过功能匹配来保护隐私的身份验证模型

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摘要

Many forms of biometrics have been proposed and studied for biometrics authentication. Recently researchers are looking into longitudinal pattern matching that based on more than just a singular biometrics; data from user's activities are used to characterise the identity of a user. In this paper we advocate a novel type of authentication by using a user's medical history which can be electronically stored in a biometric security card. This is a sequel paper from our previous work about defining abstract format of medical data to be queried and tested upon authentication. The challenge to overcome is preserving the user's privacy by choosing only the useful features from the medical data for use in authentication. The features should contain less sensitive elements and they are implicitly related to the target illness. Therefore exchanging questions and answers about a few carefully chosen features in an open channel would not easily or directly expose the illness, but yet it can verify by inference whether the user has a record of it stored in his smart card. The design of a privacy preserving model by backward inference is introduced in this paper. Some live medical data are used in experiments for validation and demonstration.
机译:已经提出并研究了许多形式的生物识别技术以用于生物识别认证。最近,研究人员正在研究基于不仅仅是单一生物特征的纵向模式匹配。来自用户活动的数据用于表征用户身份。在本文中,我们提倡使用用户的病历进行新型身份验证,该病历可以电子方式存储在生物特征安全卡中。这是我们先前工作的续篇,内容涉及定义要通过身份验证进行查询和测试的医学数据的抽象格式。要克服的挑战是通过从医疗数据中仅选择有用的功能以进行身份​​验证来保护用户的隐私。这些特征应包含不太敏感的元素,并且与目标疾病隐式相关。因此,在公开渠道中交换有关一些精心选择的功能的问题和答案不会轻易或直接暴露疾病,但是它可以通过推断来验证用户是否在智能卡中存储了该疾病的记录。介绍了一种基于反向推理的隐私保护模型设计。实验中使用了一些实时医疗数据进行验证和演示。

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