Modelling and simulation of a biometric identity-based cryptography

Government information is a vital asset that must be kept in a trusted environment and efficiently managed by authorised parties. Even though e-Government provides a number of advantages, it also introduces a range of new security risks. Sharing confidential and top-secret information in a secure manner among government sectors tend to be the main element that government agencies look for. Thus, developing an effective methodology is essential and it is a key factor for e-Government success. The proposed e-Government scheme in this paper is a combination of identity-based encryption and biometric technology. This new scheme can effectively improve the security in authentication systems, which provides a reliable identity with a high degree of assurance. In addition, this paper demonstrates the feasibility of using Finite-state machines as a formal method to analyse the proposed protocols

Performance Evaluation of Biometric Template Update

Template update allows to modify the biometric reference of a user while he uses the biometric system. With such kind of mechanism we expect the biometric system uses always an up to date representation of the user, by capturing his intra-class (temporary or permanent) variability. Although several studies exist in the literature, there is no commonly adopted evaluation scheme. This does not ease the comparison of the different systems of the literature. In this paper, we show that using different evaluation procedures can lead in different, and contradictory, interpretations of the results. We use a keystroke dynamics (which is a modality suffering of template ageing quickly) template update system on a dataset consisting of height different sessions to illustrate this point. Even if we do not answer to this problematic, it shows that it is necessary to normalize the template update evaluation procedures.Comment: International Biometric Performance Testing Conference 2012, Gaithersburg, MD, USA : United States (2012

Hybrid Template Update System for Unimodal Biometric Systems

Semi-supervised template update systems allow to automatically take into account the intra-class variability of the biometric data over time. Such systems can be inefficient by including too many impostor's samples or skipping too many genuine's samples. In the first case, the biometric reference drifts from the real biometric data and attracts more often impostors. In the second case, the biometric reference does not evolve quickly enough and also progressively drifts from the real biometric data. We propose a hybrid system using several biometric sub-references in order to increase per- formance of self-update systems by reducing the previously cited errors. The proposition is validated for a keystroke- dynamics authentication system (this modality suffers of high variability over time) on two consequent datasets from the state of the art.Comment: IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS 2012), Washington, District of Columbia, USA : France (2012

A Survey on Ear Biometrics

Recognizing people by their ear has recently received significant attention in the literature. Several reasons account for this trend: first, ear recognition does not suffer from some problems associated with other non contact biometrics, such as face recognition; second, it is the most promising candidate for combination with the face in the context of multi-pose face recognition; and third, the ear can be used for human recognition in surveillance videos where the face may be occluded completely or in part. Further, the ear appears to degrade little with age. Even though, current ear detection and recognition systems have reached a certain level of maturity, their success is limited to controlled indoor conditions. In addition to variation in illumination, other open research problems include hair occlusion; earprint forensics; ear symmetry; ear classification; and ear individuality. This paper provides a detailed survey of research conducted in ear detection and recognition. It provides an up-to-date review of the existing literature revealing the current state-of-art for not only those who are working in this area but also for those who might exploit this new approach. Furthermore, it offers insights into some unsolved ear recognition problems as well as ear databases available for researchers

Predictive biometrics: A review and analysis of predicting personal characteristics from biometric data

Interest in the exploitation of soft biometrics information has continued to develop over the last decade or so. In comparison with traditional biometrics, which focuses principally on person identification, the idea of soft biometrics processing is to study the utilisation of more general information regarding a system user, which is not necessarily unique. There are increasing indications that this type of data will have great value in providing complementary information for user authentication. However, the authors have also seen a growing interest in broadening the predictive capabilities of biometric data, encompassing both easily definable characteristics such as subject age and, most recently, `higher level' characteristics such as emotional or mental states. This study will present a selective review of the predictive capabilities, in the widest sense, of biometric data processing, providing an analysis of the key issues still adequately to be addressed if this concept of predictive biometrics is to be fully exploited in the future

Pseudo Identities Based on Fingerprint Characteristics

This paper presents the integrated project TURBINE which is funded under the EU 7th research framework programme. This research is a multi-disciplinary effort on privacy enhancing technology, combining innovative developments in cryptography and fingerprint recognition. The objective of this project is to provide a breakthrough in electronic authentication for various applications in the physical world and on the Internet. On the one hand it will provide secure identity verification thanks to fingerprint recognition. On the other hand it will reliably protect the biometric data through advanced cryptography technology. In concrete terms, it will provide the assurance that (i) the data used for the authentication, generated from the fingerprint, cannot be used to restore the original fingerprint sample, (ii) the individual will be able to create different "pseudo-identities" for different applications with the same fingerprint, whilst ensuring that these different identities (and hence the related personal data) cannot be linked to each other, and (iii) the individual is enabled to revoke an biometric identifier (pseudo-identity) for a given application in case it should not be used anymore

SuperIdentity: fusion of identity across real and cyber domains

Under both benign and malign circumstances, people now manage a spectrum of identities across both real-world and cyber domains. Our belief, however, is that all these instances ultimately track back for an individual to reflect a single ‘SuperIdentity’. This paper outlines the assumptions underpinning the SuperIdentity Project, describing the innovative use of data fusion to incorporate novel real-world and cyber cues into a rich framework appropriate for modern identity. The proposed combinatorial model will support a robust identification or authentication decision, with confidence indexed both by the level of trust in data provenance, and the diagnosticity of the identity factors being used. Additionally, the exploration of correlations between factors may underpin the more intelligent use of identity information so that known information may be used to predict previously hidden information. With modern living supporting the ‘distribution of identity’ across real and cyber domains, and with criminal elements operating in increasingly sophisticated ways in the hinterland between the two, this approach is suggested as a way forwards, and is discussed in terms of its impact on privacy, security, and the detection of threa