154 research outputs found
The role of handwritten signature verification in multi-modal biometric security systems
No full textBiometric technologies provide important components in thedevelopment of systems for the regulation of on-line information access. Significant application areas exist and continue to grow for these technologies. In this invited paper, a number of key issues will be addressed concerning handwriting verification and its place within a multi-modal biometric system. We shall identify some strategies and techniques for improving the reliability of the handwritten signature as a biometric modality based on a modular approach to feature analysis. We shall provide an overview of current developments in automatic signature verification, in particular defining research strands which are likely to support the translation of robust signature verification techniques from the laboratory to the market place. A number of current research topics in automatic signature verification will be covered including issues in assembling a database of “live” signature samples, enrolment validation and management of system design complexity
Biometric Liveness Detection Using Gaze Information
No full textThis thesis is concerned with liveness detection for biometric systems and in particular for face recognition systems. Biometric systems are well studied and have the potential to provide satisfactory solutions for a variety of applications.
However, presentation attacks (spoofng), where an attempt is made at subverting them system by making a deliberate presentation at the sensor is a serious challenge to their use in unattended applications. Liveness detection techniques can help with protecting biometric systems from attacks made through the presentation of artefacts and recordings at the sensor. In this work novel techniques for liveness detection are presented using gaze information.
The notion of natural gaze stability is introduced and used to develop a number of novel features that rely on directing the gaze of the user and establishing its behaviour. These features are then used to develop systems for detecting spoofng attempts. The attack scenarios considered in this work include the use of hand held photos and photo masks as well as video reply to subvert the system. The proposed features and systems based on them were evaluated extensively using data captured from genuine and fake attempts.
The results of the evaluations indicate that gaze-based features can be used to discriminate between genuine and imposter. Combining features through feature selection and score fusion substantially improved the performance of the proposed features
Intelligent Agents for the Management of Complexity in Multimodal Biometrics
No full textCurrent approaches to personal identity authentication using a single biometric technology are limited, principally because no single biometric is generally considered both sufficiently accurate and user-acceptable for universal application. Multimodal biometrics can provide a more adaptable solution to the security and convenience requirements of many applications. However, such an approach can also lead to additional complexity in the design and management of authentication systems. Additionally, complex hierarchies of security levels and interacting user/provider requirements demand that authentication systems are adaptive and flexible in configuration.
In this paper we consider the integration of multimodal biometrics using intelligent agents to address issues of complexity management. The work reported here is part of a major project designated IAMBIC (Intelligent Agents for Multimodal Biometric Identification and Control), aimed at exploring the application of the intelligent agent metaphor to the field of biometric authentication. The paper provides an introduction to a first-level architecture for such a system, and demonstrates how this architecture can provide a framework for the effective control and management of access to data and systems where issues of privacy, confidentiality and trust are of primary concern. Novel approaches to software agent design and agent implementation strategies required for this architecture are also highlighted. The paper further shows how such a structure can define a fundamental paradigm to support the realisation of “universal access” in situations where data integrity and confidentiality must be robustly and reliably protected .
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The Use of EEG Signals For Biometric Person Recognition
No full textThis work is devoted to investigating EEG-based biometric recognition systems. One potential advantage of using EEG signals for person recognition is the difficulty in generating artificial signals with biometric characteristics, thus making the spoofing of EEG-based biometric systems a challenging task. However, more works needs to be done to overcome certain drawbacks that currently prevent the adoption of EEG biometrics in real-life scenarios: 1) usually large number of employed sensors, 2) still relatively low recognition rates (compared with some other biometric modalities), 3) the template ageing effect.
The existing shortcomings of EEG biometrics and their possible solutions are addressed from three main perspectives in the thesis: pre-processing, feature extraction and pattern classification. In pre-processing, task (stimuli) sensitivity and noise removal are investigated and discussed in separated chapters. For feature extraction, four novel features are proposed; for pattern classification, a new quality filtering method, and a novel instance-based learning algorithm are described in respective chapters. A self-collected database (Mobile Sensor Database) is employed to investigate some important biometric specified effects (e.g. the template ageing effect; using low-cost sensor for recognition).
In the research for pre-processing, a training data accumulation scheme is developed, which improves the recognition performance by combining the data of different mental tasks for training; a new wavelet-based de-noising method is developed, its effectiveness in person identification is found to be considerable. Two novel features based on Empirical Mode Decomposition and Hilbert Transform are developed, which provided the best biometric performance amongst all the newly proposed features and other state-of-the-art features reported in the thesis; the other two newly developed wavelet-based features, while having slightly lower recognition accuracies, were computationally more efficient. The quality filtering algorithm is designed to employ the most informative EEG signal segments: experimental results indicate using a small subset of the available data for feature training could receive reasonable improvement in identification rate. The proposed instance-based template reconstruction learning algorithm has shown significant effectiveness when tested using both the publicly available and self-collected databases
Using Biometrics as an Enabling Technology in Balancing Universality and Selectivity for Management of Information Access
No full textThe key concept of Universal Access in the Information Society has important and far-reaching implications for the design of a wide range of systems and data sources. This paper sets out to examine two fundamentally conflicting aspects of the broad principle of universality in design, pointing to the opposite requirement that, in many applications, access to a. system or set of data must be limited to an identifiable population of "authorised" users. However, the idea of universality then applies at a lower level, since the mechanisms used to impose these limitations should themselves not be dependent on the physical attributes or expertise of individuals, but rather related to their identity and designated level of authorisation. This leads to an interesting situation where the concept of universality must be implemented at different levels and, equally, must be balanced against the competing claims of the constraints imposed by authorisation-determined selectivity. This paper argues that technology based on biometric processing - the exploitation of measurements relating to individual physiological or behavioural attributes provides a key platform on which an access management structure can be realised. Experimental results based on various biometric modalities are used to support and illustrate the ideas proposed
Design of multimodal biometric systems for universal authentication and access control
No full textCurrent approaches to the use of single biometrics in personal identity authentication are limited, principally because no single biometric is generally considered both sufficiently accurate and user-acceptable for universal application. Multimodal biometrics can provide a more balanced solution to the security and convenience requirements of many applications. However, such an approach can also lead to additional complexity in the design and management of authentication systems. Additionally, complex hierarchies of security levels and interacting user/provider requirements demand that a system is adaptive and flexible in configuration. In this paper we consider the integration of multi-modal biometrics using intelligent agents to address these issues of complexity management. The work reported here is part of a major project designated IAMBIC (Intelligent Agents for Multimodal Biometric Identification and Control) aimed at exploring the application of the intelligent agent metaphor to the field of biometric authentication
Nineteen Urgent Research Topics in Biometrics and Identity Management
No full textBiometric technologies are being increasingly deployed in practical applications but are currently mainly driven by governmental initiatives, ranging from border control applications to national ID programmes, with increasing social and legal impact on everyday’s life. However, biometrics offer wider opportunities and their application as enabling technology for modern identity management systems, having a more user-centred approach, will be more important in the near future. In this paper we give an overview of the most important research topics for Biometrics and Identity Management for the near future
Spoofing attempt detection using gaze colocation
No full textSpoofing attacks on biometric systems are one of the major impediments to their use for secure unattended applications. This paper presents a novel method for face liveness detection by tracking the gaze of the user with an ordinary webcam. In the proposed system, an object appears randomly on the display screen which the user is required to look at while their gaze is measured. The visual stimulus appears in such a way that it repeatedly directs the gaze of the user to specific points on the screen. Features extracted from images captured at these sets of colocated points are used to estimate the liveness of the user. A scenario is investigated where genuine users track the challenge with head/eye movements whereas the impostors hold a photograph of the target user and attempt to follow the stimulus during simulated spoofing attacks. The results from the experiments indicate the effectiveness of the gaze colocation feature in detecting spoofing attac
Directional Sensitivity of Gaze-Collinearity Features in Liveness Detection
No full textTo increase the trust in using face recognition systems, these need to be capable of differentiating between face images captured from a real person and those captured from photos or similar artifacts presented at the sensor. Methods have been published for face liveness detection by measuring the gaze of a user while the user tracks an object on the screen, which appears at pre-defined, places randomly. In this paper we explore the sensitivity of such a system to different stimulus alignments. The aim is to establish whether there is such sensitivity and if so to explore how this may be exploited for improving the design of the stimulus. The results suggest that collecting feature points along the horizontal direction is more effective than the vertical direction for liveness detection
A memetic fingerprint matching algorithm
No full textMinutiae point pattern matching is the most common approach for fingerprint verification. Although many minutiae point pattern matching algorithms have been proposed, reliable automatic fingerprint verification remains as a challenging problem, both with respect to recovering the optimal alignment and the construction of an adequate matching function. In this paper, we develop a memetic fingerprint matching algorithm (MFMA) which aims to identify the optimal or near optimal global matching, between two minutiae sets. Within the MFMA, we first introduce an efficient matching operation to produce an initial population of local alignment configurations by examining local features of minutiae. Then, we devise a hybrid evolutionary procedure by combining the use of the global search functionality of a genetic algorithm with a local improvement operator to search for the optimal or near optimal global alignment. Finally, we define a reliable matching function for fitness computation. The proposed algorithm was evaluated by means of a series of experiments conducted on the FVC2002 database and compared with previous work. Experimental results confirm that the MFMA is an effective and practical matching algorithm for fingerprint verification. The algorithm is faster and more accurate than a traditional genetic-algorithm-based method. It is also more accurate than a number of other methods implemented for comparison, though our method generally requires more computational time in performing fingerprint matching
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