Image Watermaking With Biometric Data For Copyright Protection

In this paper, we deal with the proof of ownership or legitimate usage of a digital content, such as an image, in order to tackle the illegitimate copy. The proposed scheme based on the combination of the watermark-ing and cancelable biometrics does not require a trusted third party, all the exchanges are between the provider and the customer. The use of cancelable biometrics permits to provide a privacy compliant proof of identity. We illustrate the robustness of this method against intentional and unintentional attacks of the watermarked content

Constructing practical Fuzzy Extractors using QIM

Fuzzy extractors are a powerful tool to extract randomness from noisy data. A fuzzy extractor can extract randomness only if the source data is discrete while in practice source data is continuous. Using quantizers to transform continuous data into discrete data is a commonly used solution. However, as far as we know no study has been made of the effect of the quantization strategy on the performance of fuzzy extractors. We construct the encoding and the decoding function of a fuzzy extractor using quantization index modulation (QIM) and we express properties of this fuzzy extractor in terms of parameters of the used QIM. We present and analyze an optimal (in the sense of embedding rate) two dimensional construction. Our 6-hexagonal tiling construction offers ( log2 6 / 2-1) approx. 3 extra bits per dimension of the space compared to the known square quantization based fuzzy extractor

Biometric Template Spoofing Detection Using Sparse Watermarking Scheme

No Abstrac

Security of Biometric Data Using Compressed Watermarking Technique

This paper has focus on biometric data security over open communication channel of biometric system. Here biometric data is encoded using cs theory and wavelet based embedding technique. The biometric data is convert into encoded sparse measurements which is generating using SVD, random seed and uniform quantization process. Then these encoded sparse measurements are embedding into the host color biometric data using wavelet based watermarking technique. This proposed technique has explored dimension reduction and computational security provided by compressive sensing. This proposed technique has also helps to compressed and to send secret data over noisy communication channel of biometric system against various attacks. The proposed technique provides more security compare to existed technique in literature due to CS theory. The novelty of proposed technique is that, watermark iris image information is compressed and encoded using CS theory and uniform quantization.DOI:http://dx.doi.org/10.11591/ijece.v4i5.664

Protecting biometric templates with image watermarking techniques

Biometric templates are subject to modifications for identity fraud especially when they are stored in databases. In this paper, a new approach to protecting biometric templates with image watermarking techniques is proposed. The novelty of this approach is that we have combined lattice and block-wise image watermarking techniques to maintain image quality along with cryptographic techniques to embed fingerprint templates into facial images and vice-versa. Thus, protecting them from being modified

A New Model of Securing Iris Authentication Using Steganography

The integration of steganography in biometric system is a solution for enhancing security in iris. The process of biometric enrollment and verification is not highly secure due to hacking activities at the biometric point system such as overriding iris template in database. In this paper, we proposed an enhancement of temporal-spatial domain algorithm which involves the scheme of Least Significant Bits (LSB) as the new model which converts iris images to binary stream and hides into a proper lower bit plane. Here, the stego key, n, will be inserted into the binary values from the plane which concealed the information; where n is the input parameter in binary values which inserted to the iris codes, m. These values produce the output which is the new iris stego image after binary conversion. Theoretically, the proposed model is promising a high security performance implementation in the future