Framework for Preservation of Biometric Information with Facial Template Protection using Gray-Level Extended Visual Cryptography Scheme

Dhara Kumari, Dr. Dinesh Kumar, Dr. Rajni Sharma


The main idea of this paper is to explore the privacy of information security and network security during the transmission of data using
the Visual Cryptography (VC) techniques onto the area of authentication using Biometrics data (face images). A face image is usually registered
in a central database as an important piece of personal information. To protect the copyright and privacy of face images, we propose a visual
cryptography for transmission of any type of information privacy to biometric data (face images, iris codes, fingerprint images etc). In which we
suggest an approach to protect the privacy of a specific face data set (known as a private face images) by encrypting its face images using face
images from another set (known as a public face images). Each private face image will be encrypted by using two host images from the public
face images via the GEVCS method based on the XOR and OR operation. . In this work, private face image is dithered into two host face images
(known as sheets) that are stored in two separate database servers(XM2VTS and IMM) such that the private image can be revealed only when
both sheets are simultaneously available; at the same time, the individual sheet images do not reveal the identity of the private image.
Experimental results show the proposed scheme not only to protect the privacy of face images in database, but also shows better robustness to
noise, filter, JPEG compression, rotation and other attacks.


Keywords: Visual Cryptography, Biometric Data, Private Face, Public Face, GEVCS, XM2VTS, IMM, Privacy, OR operator.

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