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Reliable Identity Management System Using Raspberry Pi

机译:使用覆盆子PI可靠的身份管理系统

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Biometric authentication, the process of verification using unique biological characteristics, is considered one of the most accurate technologies for authentication. It compares two or more biometric data to identify the differences among them properly. Based on the comparison between individual’s biometric features and stored authorized features, it makes the decision of matched or mismatched. If the given sample of the biometric data matches with the stored one, authorization is confirmed. Nowadays, many real-time applications use biometric authentication to meet security purposes fully. However, it is difficult to implement fingerprint recognition system specially on Linux based computer. A well-known, less costly embedded computer called Raspberry Pi is used to build the entire system. Fingerprint enrollment, fingerprint recognition, photo capture, QR code generation as well as QR code reading were entirely done using python and python associated libraries. For storage management, we have used MySQL as it is convenient and open-source. This paper discusses about a quality authentication model which is highly capable and cost- effective. The authentication process consists of extracting the biometric features with ORB algorithm, matching those features using FLANN matcher, generating and validating QR code based on encrypted personal information accurately. Here, AES algorithm is used for encrypting personal data which is then converted and stored in form of QR code. Final authentication process involves both fingerprint and QR code validation. Performing two factor authentication affixes more reliability to the system.
机译:生物识别认证,使用独特的生物特性验证过程被认为是认证最准确的技术之一。它比较了两个或更多的生物识别数据来正确识别它们之间的差异。基于个体的生物识别功能与存储授权功能之间的比较,实现匹配或不匹配的决定。如果生物识别数据的给定示例与存储的数据匹配,则确认授权。如今,许多实时应用程序使用生物识别身份验证完全满足安全目的。但是,难以专门用于基于Linux计算机的指纹识别系统。众所周知的,较低昂贵的嵌入式计算机称为覆盆子PI,用于构建整个系统。指纹注册,指纹识别,照片捕获,QR码生成以及QR码读数完全使用Python和Python关联库完成。对于存储管理,我们使用MySQL,因为它是方便和开源的。本文讨论了质量认证模型,该模型具有高度能力和经济效益。身份验证过程包括用ORB算法提取生物识别功能,使用FLANN匹配器匹配这些功能,基于加密的个人信息,基于加密的个人信息进行准确地生成和验证QR码。这里,AES算法用于加密个人数据,然后以QR码的形式转换和存储。最终身份验证过程涉及指纹和QR码验证。执行两个因子认证对系统的更可靠性。

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