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Securing recognized multimodal biometric images using cryptographic model

机译:使用加密模型确保已识别的多模式生物识别图像

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摘要

The security of recognized biometric images keeps sensitive data from the vindictive behavior in transmission. An optional technique to guarantee the secrecy and abnormal state of security is cryptography. The protection of biometrics images raises significant worries, specifically if calculations over biometric information are performed at untrusted servers. In our previous work, the multimodal biometric images are recognized dependent on optimal features. To ensure these recognized images, a cryptographic strategy is proposed in this investigation. At first, the recognized images are given to the progressive cryptographic method which is utilized to the secret image is shared safely and furthermore, its data is kept up with the most extreme classification. In this research work, various shadows have been produced from one image with the assistance of the Visual Shadow Creation (VSC) Process. The different shadows are utilized to move the secret image by utilizing the encryption and decoding process by methods for Elliptic Curve Cryptography (ECC). The proposed method offers better security for shadows and reduced the fraudulent shares of the secret image. The performance investigation of the proposed cryptographic demonstrates the high security, adequacy, and power compared with existing cryptographic algorithms. The abovementioned systems are actualized in MATLAB programming.
机译:公认的生物识别图像的安全性会使传输中的报复行为保持敏感的数据。一种保证保密性和安全状态的可选技术是加密。生物识别图像的保护提高了显着的担忧,具体是在不受信用的服务器上执行生物识别信息的计算。在我们以前的工作中,多模式生物识别图像被识别取决于最佳特征。为确保这些公认的图像,在这项调查中提出了一种加密策略。首先,识别的图像被提供给被安全地共享秘密图像的逐行加密方法,并且其数据保持了最极端的分类。在这项研究工作中,在视觉阴影创建(VSC)过程的帮助下,从一个图像中生产了各种阴影。利用不同的阴影来通过利用椭圆曲线密码(ECC)的方法来利用加密和解码处理来移动秘密图像。该方法为阴影提供了更好的安全性,并减少了秘密图像的欺诈性份额。与现有的加密算法相比,提出的加密的性能调查展示了高安全性,充分性和功率。上述系统是在MATLAB编程中实现的。

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