Enhancing security for multimodal biometric using Hyper Image Encryption Algorithm

K. Nivetha, D. Saraswady
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引用次数: 2

Abstract

The deployment of large-scale biometric systems in both commercial and government applications has served to increase the public's awareness of this technology. This dramatic growth in biometric system has clearly highlighted the challenges associated in designing and integrating these systems. `Multimodal biometrics' is development to great importance wherein the information from three different biometric sources namely finger print, retina, finger vein is used for authentication system. Unlike unibiometric systems, these are sensitive to noise and make spoofing difficult for hackers. As an deployment of multimodal biometric, this project aims to dynamically ensure the performance to provide an enhanced level of security by combining Finger vein, Retina and Fingerprint with Hyper Image Encryption Algorithm (HIEA). Hyper image encryption algorithm is applied to the biometric template and only the transformed template is stored in the database based on secret key in which increases GAR and reduces FAR.
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利用超图像加密算法提高多模态生物识别的安全性
在商业和政府应用中大规模部署生物识别系统,有助于提高公众对这项技术的认识。生物识别系统的急剧增长明显地突出了设计和集成这些系统所面临的挑战。“多模式生物识别技术”的发展非常重要,其中来自三种不同生物识别来源的信息,即指纹,视网膜,手指静脉用于身份验证系统。与单一生物识别系统不同,这些系统对噪音很敏感,黑客很难进行欺骗。作为多模态生物识别技术的一个部署,本项目旨在通过将手指静脉、视网膜和指纹与超图像加密算法(HIEA)相结合,动态确保性能,提供更高的安全性。采用超图像加密算法对生物特征模板进行加密,仅将转换后的模板存储在基于密钥的数据库中,提高了GAR,降低了FAR。
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