Visual Communication and Image Representation; Researchers at Multimedia University publish new data on visual communication and image representation

2010 MAY 18 - ( NewsRx.com) -- According to recent research published in the Journal of Visual Communication and Image Representation, "Contemporary fingerprint system uses solid flat sensor which requires contact of the finger on a platen surface (see also Visual Communication and Image Representation). This often results in several problems such as image deformation, durability weakening in the sensor, latent fingerprint issues which can lead to forgery and hygienic problems.

Random Multispace Quantization as an Analytic Mechanism for BioHashing of Biometric and Random Identity Inputs

Biometric analysis for identity verification is becoming a widespread reality. Such implementations necessitate large-scale capture and storage of biometric data, which raises serious issues in terms of data privacy and (if such data is compromised) identity theft. These problems stem from the essential permanence of biometric data, which (unlike secret passwords or physical tokens) cannot be refreshed or reissued if compromised. Our previously presented biometric-hash framework prescribes the integration of external (password or token-derived) randomness with user-specific biometrics, resulting in bitstring outputs with security characteristics (i.e., noninvertibility) comparable to cryptographic ciphers or hashes. The resultant BioHashes are hence cancellable, i.e., straightforwardly revoked and reissued (via refreshed password or reissued token) if compromised. BioHashing furthermore enhances recognition effectiveness, which is explained in this paper as arising from the Random Multispace Quantization (RMQ) of biometric and external random inputs

Biometric hash: high-confidence face recognition

In this paper, we describe a biometric hash algorithm for robust extraction of bits from face images. While a face-recognition system has high acceptability, its accuracy is low. The problem arises because of insufficient capability of representing features and variations in data. Thus, we use dimensionality reduction to improve the capability to represent features, error correction to improve robustness with respect to within-class variations, and random projection and orthogonalization to improve discrimination among classes. Specifically, we describe several dimensionality-reduction techniques with biometric hashing enhancement for various numbers of bits extracted. The theoretical results are evaluated on the FERET face database showing that the enhanced methods significantly outperform the corresponding raw methods when the number of extracted bits reaches 100. The improvements of the postprocessing stage for principal component analysis (PCA), Wavelet Transform with PCA, Fisher linear discriminant, Wavelet Transform, and Wavelet Transform with Fourier-Mellin Transform are 98.02%, 95.83%, 99.46%, 99.16%, and 100%, respectively. The proposed technique is quite general, and can be applied to other biometric templates. We anticipate that this algorithm will find applications in cryptographically secure biometric authentication schemes

A security- and privacy-driven hybrid biometric template protection technique

Biometric template protection techniques are used to secure biometric templates from various attacks and threats. As the trade-off between the performance and the security and privacy of said techniques has drawn increasing concerns from the researchers, a single approach can no longer satisfy the elevated requirement. In this paper, a state-of-the-art hybrid template protection method, called the cancelable secure sketch (CaSS) is proposed. The concept of CaSS is demonstrated via a cancelable fingerprint, namely the multi-line code (MLC) with the code-offset construction of secure sketch. The proposed method boasts high security and privacy by virtue of the revocability of MLC. Besides, inheriting the high performance of binary MLC, the CaSS method is able to achieve 0% FRR and FAR

Privacy Protection of Biometric Templates

Although many biometric characteristics are not secrets, biometric reference data (also known as biometric templates) need to be stored securely and to be protected against unauthorized use. For this purpose, biometric template protection techniques have been developed that do not only prevent privacy leakage and provide confidentiality of the stored biometric templates, but address also problems like identity theft and cross-matching of biometric templates stored in different systems. This paper describes the security and privacy risks associated with storing biometric data and highlights the necessity of using biometric template protection as a potential remedy to these risks. Privacy considerations are discussed with respect to using fingerprint verification for access control to a public outdoor swimming pool

Two-Factor Authentication or How to Potentially Counterfeit Experimental Results in Biometric Systems

Two-factor authentication has been introduced in order to enhance security in authentication systems. Different factors have been introduced, which are combined for means of controlling access. The increasing demand for high security applications has led to a growing interest in biometrics. As a result several two-factor authentication systems are designed to include biometric authentication. In this work the risk of result distortion during performance evaluations of two-factor authentication systems including biometrics is pointed out. Existing approaches to two-factor biometric authentication systems are analyzed. Based on iris biometrics a case study is presented, which demonstrates the trap of untruly increasing recognition rates by introducing a second authentication factor to a biometric authentication system. Consequently, several requirements for performance evaluations of two-factor biometric authentication systems are stated