FFT-Based Zero-Bit Watermarking for Facial Recognition and Its Security
01 Jan 2021-pp 403-417
TL;DR: In this paper, the design of zero-bit watermarking in which a user's unique id is integrated with his facial features in the multi-transform domain is presented. And the model is indeed satisfying security of the host biometric of the user.
Abstract: The security of a system through biometric features is one of the acceptable trends to which every researcher recommends. Such biometric features contain features of iris, fingerprint, face, etc. Today, these security traits are widely exploited by an imposter to trace unlicensed access to the system. So it demands to secure these features since foremost alarming challenges are raises when these trustworthy features are compromised. This paper endorses the design of zero-bit watermarking in which a user’s unique id is integrated with his facial features in the multi-transform domain. The user’s unique ID is used to establish true authentication of the host facial features and also to recognize the face without any segmentation techniques. To make this effort tangible, Singular values are calculated of some particular frequency coefficients of the host image that are generated using FFT transformation in which a number of appropriate regions of the host image are selected based on their frequency of information. These Singular values of host facial image are calculated using SVD in which watermark (image) user’s unique ID is integrated correctly while maintaining the equilibrium among imperceptibility, robustness, and payload. The resultant watermarked image is tested against various image processing attacks and satisfying results are conducted to assure robustness of the model. Thus, the model is indeed satisfying security of the host biometric of the user.
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TL;DR: The obtained results show that the approach offers good imperceptibility and generates watermarking images robust against various attacks with a high-quality watermark.
102 citations
TL;DR: An overview of steganography techniques applied in the protection of biometric data in fingerprints is presented and the strengths and weaknesses of targeted and blind steganalysis strategies for breaking steganographers techniques are discussed.
Abstract: Identification of persons by way of biometric features is an emerging phenomenon. Over the years, biometric recognition has received much attention due to its need for security. Amongst the many existing biometrics, fingerprints are considered to be one of the most practical ones. Techniques such as watermarking and steganography have been used in attempt to improve security of biometric data. Watermarking is the process of embedding information into a carrier file for the protection of ownership/copyright of music, video or image files, whilst steganography is the art of hiding information. This paper presents an overview of steganography techniques applied in the protection of biometric data in fingerprints. It is novel in that we also discuss the strengths and weaknesses of targeted and blind steganalysis strategies for breaking steganography techniques.
92 citations
TL;DR: A zero-watermark scheme using RST invariant features, the SVM and the PSO algorithm against RST attacks for image authentication and the experimental results show that the SZW method outperforms other existing methods against R ST attacks under consideration here.
68 citations
TL;DR: A zero-watermarking scheme implemented in the composite Contourlet Transform (CT)—Singular Value Decomposition (SVD) domain for unambiguous authentication of medical images and access to patient records is presented.
Abstract: Healthcare institutions adapt cloud based archiving of medical images and patient records to share them efficiently. Controlled access to these records and authentication of images must be enforced to mitigate fraudulent activities and medical errors. This paper presents a zero-watermarking scheme implemented in the composite Contourlet Transform (CT)—Singular Value Decomposition (SVD) domain for unambiguous authentication of medical images. Further, a framework is proposed for accessing patient records based on the watermarking scheme. The patient identification details and a link to patient data encoded into a Quick Response (QR) code serves as the watermark. In the proposed scheme, the medical image is not subjected to degradations due to watermarking. Patient authentication and authorized access to patient data are realized on combining a Secret Share with the Master Share constructed from invariant features of the medical image. The Hu's invariant image moments are exploited in creating the Master Share. The proposed system is evaluated with Checkmark software and is found to be robust to both geometric and non geometric attacks.
66 citations
11 Apr 2007
TL;DR: Through using individual unique iris features for biometric watermarking information and secondary authentication, the security level is much enhanced and the legal responsibility problem about the outflow of face data can be solved.
Abstract: In this paper, we propose a new iris feature watermarking method on face data. This research has following three objectives. First, by using watermarked iris features in addition to face data, the multimodal biometric authentication can be possible, which can increase the authentication accuracy. Second, in case that the saved face data is illegally let out and privacy infringement happens, by checking the inserted iris feature watermark, we can solve the legal responsibility problem about the outflow of face data. In detail, if the iris feature watermark cannot be extracted from the outflow face data, we can insist that the face data is let out from other organization instead of ours. Third, in case that "the iris features need to be transmitted via non-secure and noisy communication channel" [1], it can be invisibly hidden on face data by our method. For the first objective, the face recognition accuracy with iris feature watermark should not be degraded. For the second and third objectives, the inserted iris watermark should be "strong" enough to be extracted irrespective of various kinds of attacks (such as blurring, cropping and rotation attacks) and noise insertion on face data. This research has three advantages compared to previous works. First, to overcome the vulnerability of blurring attack to previous biometric watermarking based on spatial domain, we use the watermarking method in frequency domain. Second, to reduce the degradation of face recognition accuracy due to iris watermarking, we insert the watermark into mid and high frequency bands. Third, through using individual unique iris features for biometric watermarking information and secondary authentication, the security level is much enhanced and we can solve legal responsibility problem about the outflow of face data. Experimental results showed that our algorithm could be used to accomplish above objectives.
63 citations