Authentication of Students and Students’ Work in E-Learning : Report for the Development Bid of Academic Year 2010/11

Global e-learning market is projected to reach $107.3 billion by 2015 according to a new report by The Global Industry Analyst (Analyst 2010). The popularity and growth of the online programmes within the School of Computer Science obviously is in line with this projection. However, also on the rise are students’ dishonesty and cheating in the open and virtual environment of e-learning courses (Shepherd 2008). Institutions offering e-learning programmes are facing the challenges of deterring and detecting these misbehaviours by introducing security mechanisms to the current e-learning platforms. In particular, authenticating that a registered student indeed takes an online assessment, e.g., an exam or a coursework, is essential for the institutions to give the credit to the correct candidate. Authenticating a student is to ensure that a student is indeed who he says he is. Authenticating a student’s work goes one step further to ensure that an authenticated student indeed does the submitted work himself. This report is to investigate and compare current possible techniques and solutions for authenticating distance learning student and/or their work remotely for the elearning programmes. The report also aims to recommend some solutions that fit with UH StudyNet platform.Submitted Versio

Biometric Spoofing: A JRC Case Study in 3D Face Recognition

Based on newly available and affordable off-the-shelf 3D sensing, processing and printing technologies, the JRC has conducted a comprehensive study on the feasibility of spoofing 3D and 2.5D face recognition systems with low-cost self-manufactured models and presents in this report a systematic and rigorous evaluation of the real risk posed by such attacking approach which has been complemented by a test campaign. The work accomplished and presented in this report, covers theories, methodologies, state of the art techniques, evaluation databases and also aims at providing an outlook into the future of this extremely active field of research.JRC.G.6-Digital Citizen Securit

Forensic Face Recognition: A Survey

Beside a few papers which focus on the forensic aspects of automatic face recognition, there is not much published about it in contrast to the literature on developing new techniques and methodologies for biometric face recognition. In this report, we review forensic facial identification which is the forensic experts‟ way of manual facial comparison. Then we review famous works in the domain of forensic face recognition. Some of these papers describe general trends in forensics [1], guidelines for manual forensic facial comparison and training of face examiners who will be required to verify the outcome of automatic forensic face recognition system [2]. Some proposes theoretical framework for application of face recognition technology in forensics [3] and automatic forensic facial comparison [4, 5]. Bayesian framework is discussed in detail and it is elaborated how it can be adapted to forensic face recognition. Several issues related with court admissibility and reliability of system are also discussed. \ud Until now, there is no operational system available which automatically compare image of a suspect with mugshot database and provide result usable in court. The fact that biometric face recognition can in most cases be used for forensic purpose is true but the issues related to integration of technology with legal system of court still remain to be solved. There is a great need for research which is multi-disciplinary in nature and which will integrate the face recognition technology with existing legal systems. In this report we present a review of the existing literature in this domain and discuss various aspects and requirements for forensic face recognition systems particularly focusing on Bayesian framework

Vulnerability assessment in the use of biometrics in unsupervised environments

Mención Internacional en el título de doctorIn the last few decades, we have witnessed a large-scale deployment of biometric systems in different life applications replacing the traditional recognition methods such as passwords and tokens. We approached a time where we use biometric systems in our daily life. On a personal scale, the authentication to our electronic devices (smartphones, tablets, laptops, etc.) utilizes biometric characteristics to provide access permission. Moreover, we access our bank accounts, perform various types of payments and transactions using the biometric sensors integrated into our devices. On the other hand, different organizations, companies, and institutions use biometric-based solutions for access control. On the national scale, police authorities and border control measures use biometric recognition devices for individual identification and verification purposes. Therefore, biometric systems are relied upon to provide a secured recognition where only the genuine user can be recognized as being himself. Moreover, the biometric system should ensure that an individual cannot be identified as someone else. In the literature, there are a surprising number of experiments that show the possibility of stealing someone’s biometric characteristics and use it to create an artificial biometric trait that can be used by an attacker to claim the identity of the genuine user. There were also real cases of people who successfully fooled the biometric recognition system in airports and smartphones [1]–[3]. That urges the necessity to investigate the potential threats and propose countermeasures that ensure high levels of security and user convenience. Consequently, performing security evaluations is vital to identify: (1) the security flaws in biometric systems, (2) the possible threats that may target the defined flaws, and (3) measurements that describe the technical competence of the biometric system security. Identifying the system vulnerabilities leads to proposing adequate security solutions that assist in achieving higher integrity. This thesis aims to investigate the vulnerability of fingerprint modality to presentation attacks in unsupervised environments, then implement mechanisms to detect those attacks and avoid the misuse of the system. To achieve these objectives, the thesis is carried out in the following three phases. In the first phase, the generic biometric system scheme is studied by analyzing the vulnerable points with special attention to the vulnerability to presentation attacks. The study reviews the literature in presentation attack and the corresponding solutions, i.e. presentation attack detection mechanisms, for six biometric modalities: fingerprint, face, iris, vascular, handwritten signature, and voice. Moreover, it provides a new taxonomy for presentation attack detection mechanisms. The proposed taxonomy helps to comprehend the issue of presentation attacks and how the literature tried to address it. The taxonomy represents a starting point to initialize new investigations that propose novel presentation attack detection mechanisms. In the second phase, an evaluation methodology is developed from two sources: (1) the ISO/IEC 30107 standard, and (2) the Common Evaluation Methodology by the Common Criteria. The developed methodology characterizes two main aspects of the presentation attack detection mechanism: (1) the resistance of the mechanism to presentation attacks, and (2) the corresponding threat of the studied attack. The first part is conducted by showing the mechanism's technical capabilities and how it influences the security and ease-of-use of the biometric system. The second part is done by performing a vulnerability assessment considering all the factors that affect the attack potential. Finally, a data collection is carried out, including 7128 fingerprint videos of bona fide and attack presentation. The data is collected using two sensing technologies, two presentation scenarios, and considering seven attack species. The database is used to develop dynamic presentation attack detection mechanisms that exploit the fingerprint spatio-temporal features. In the final phase, a set of novel presentation attack detection mechanisms is developed exploiting the dynamic features caused by the natural fingerprint phenomena such as perspiration and elasticity. The evaluation results show an efficient capability to detect attacks where, in some configurations, the mechanisms are capable of eliminating some attack species and mitigating the rest of the species while keeping the user convenience at a high level.En las últimas décadas, hemos asistido a un despliegue a gran escala de los sistemas biométricos en diferentes aplicaciones de la vida cotidiana, sustituyendo a los métodos de reconocimiento tradicionales, como las contraseñas y los tokens. Actualmente los sistemas biométricos ya forman parte de nuestra vida cotidiana: es habitual emplear estos sistemas para que nos proporcionen acceso a nuestros dispositivos electrónicos (teléfonos inteligentes, tabletas, ordenadores portátiles, etc.) usando nuestras características biométricas. Además, accedemos a nuestras cuentas bancarias, realizamos diversos tipos de pagos y transacciones utilizando los sensores biométricos integrados en nuestros dispositivos. Por otra parte, diferentes organizaciones, empresas e instituciones utilizan soluciones basadas en la biometría para el control de acceso. A escala nacional, las autoridades policiales y de control fronterizo utilizan dispositivos de reconocimiento biométrico con fines de identificación y verificación individual. Por lo tanto, en todas estas aplicaciones se confía en que los sistemas biométricos proporcionen un reconocimiento seguro en el que solo el usuario genuino pueda ser reconocido como tal. Además, el sistema biométrico debe garantizar que un individuo no pueda ser identificado como otra persona. En el estado del arte, hay un número sorprendente de experimentos que muestran la posibilidad de robar las características biométricas de alguien, y utilizarlas para crear un rasgo biométrico artificial que puede ser utilizado por un atacante con el fin de reclamar la identidad del usuario genuino. También se han dado casos reales de personas que lograron engañar al sistema de reconocimiento biométrico en aeropuertos y teléfonos inteligentes [1]–[3]. Esto hace que sea necesario investigar estas posibles amenazas y proponer contramedidas que garanticen altos niveles de seguridad y comodidad para el usuario. En consecuencia, es vital la realización de evaluaciones de seguridad para identificar (1) los fallos de seguridad de los sistemas biométricos, (2) las posibles amenazas que pueden explotar estos fallos, y (3) las medidas que aumentan la seguridad del sistema biométrico reduciendo estas amenazas. La identificación de las vulnerabilidades del sistema lleva a proponer soluciones de seguridad adecuadas que ayuden a conseguir una mayor integridad. Esta tesis tiene como objetivo investigar la vulnerabilidad en los sistemas de modalidad de huella dactilar a los ataques de presentación en entornos no supervisados, para luego implementar mecanismos que permitan detectar dichos ataques y evitar el mal uso del sistema. Para lograr estos objetivos, la tesis se desarrolla en las siguientes tres fases. En la primera fase, se estudia el esquema del sistema biométrico genérico analizando sus puntos vulnerables con especial atención a los ataques de presentación. El estudio revisa la literatura sobre ataques de presentación y las soluciones correspondientes, es decir, los mecanismos de detección de ataques de presentación, para seis modalidades biométricas: huella dactilar, rostro, iris, vascular, firma manuscrita y voz. Además, se proporciona una nueva taxonomía para los mecanismos de detección de ataques de presentación. La taxonomía propuesta ayuda a comprender el problema de los ataques de presentación y la forma en que la literatura ha tratado de abordarlo. Esta taxonomía presenta un punto de partida para iniciar nuevas investigaciones que propongan novedosos mecanismos de detección de ataques de presentación. En la segunda fase, se desarrolla una metodología de evaluación a partir de dos fuentes: (1) la norma ISO/IEC 30107, y (2) Common Evaluation Methodology por el Common Criteria. La metodología desarrollada considera dos aspectos importantes del mecanismo de detección de ataques de presentación (1) la resistencia del mecanismo a los ataques de presentación, y (2) la correspondiente amenaza del ataque estudiado. Para el primer punto, se han de señalar las capacidades técnicas del mecanismo y cómo influyen en la seguridad y la facilidad de uso del sistema biométrico. Para el segundo aspecto se debe llevar a cabo una evaluación de la vulnerabilidad, teniendo en cuenta todos los factores que afectan al potencial de ataque. Por último, siguiendo esta metodología, se lleva a cabo una recogida de datos que incluye 7128 vídeos de huellas dactilares genuinas y de presentación de ataques. Los datos se recogen utilizando dos tecnologías de sensor, dos escenarios de presentación y considerando siete tipos de instrumentos de ataque. La base de datos se utiliza para desarrollar y evaluar mecanismos dinámicos de detección de ataques de presentación que explotan las características espacio-temporales de las huellas dactilares. En la fase final, se desarrolla un conjunto de mecanismos novedosos de detección de ataques de presentación que explotan las características dinámicas causadas por los fenómenos naturales de las huellas dactilares, como la transpiración y la elasticidad. Los resultados de la evaluación muestran una capacidad eficiente de detección de ataques en la que, en algunas configuraciones, los mecanismos son capaces de eliminar completamente algunos tipos de instrumentos de ataque y mitigar el resto de los tipos manteniendo la comodidad del usuario en un nivel alto.Programa de Doctorado en Ingeniería Eléctrica, Electrónica y Automática por la Universidad Carlos III de MadridPresidente: Cristina Conde Vila.- Secretario: Mariano López García.- Vocal: Farzin Derav

The Reed-Stanton press rig for the generation of reproducible fingermarks : towards a standardised methodology for fingermark research

In the search for better or new methods/techniques to visualise fingermarks or to analyse them exploiting their chemical content, fingermarks inter-variability may hinder the assessment of the method effectiveness. Variability is due to changes in the chemical composition of the fingermarks between different donors and within the same donor, as well as to differential contact time, pressure and angle. When validating a method or comparing it with existing ones, it is not always possible to account for this type of variability. One way to compensate for these issues is to employ, in the early stages of the method development, a device generating reproducible fingermarks. Here the authors present their take on such device, as well as quantitatively describing its performance and benefits against the manual production of marks. Finally a short application is illustrated for the use of this device, at the method developmental stages, in an emerging area of fingerprinting research concerning the retrieval of chemical intelligence from fingermarks

A statistical approach towards performance analysis of multimodal biometrics systems

Fueled by recent government mandates to deliver public functions by the use of biometrics, multimodal biometrics authentication has made rapid progress over the past a few years. Performance of multimodal biometrics systems plays a crucial role in government applications, including public security and forensic analysis. However, current performance analysis is conducted without considering the influence of noises, which may result in unreliable analytical results when noise levels change in practice. This thesis investigates the application of statistical methods in performance analysis of multimodal biometric systems. It develops an efficient and systematic approach to evaluate system performance in different situations of noise influences. Using this approach, 126 experiments are conducted with the BSSR1 dataset. The proposed approach helps to examine the performance of typical fusion methods that use different normalization and data partitioning techniques. Experiment results demonstrate that the Simple Sum fusion method working with the Min-Max normalization and Re-Substitution data partitioning yields the best overall performance in different noise conditions. In addition, further examination of the results reveals the need of systematic analysis of system performance as the performance of some fusion methods exhibits big variations when the level of noises changes and some fusion methods may produce very good performance in some application though normally unacceptable in others

Edge Enhancement from Low-Light Image by Convolutional Neural Network and Sigmoid Function

Due to camera resolution or any lighting condition, captured image are generally over-exposed or under-exposed conditions. So, there is need of some enhancement techniques that improvise these artifacts from recorded pictures or images. So, the objective of image enhancement and adjustment techniques is to improve the quality and characteristics of an image. In general terms, the enhancement of image distorts the original numerical values of an image. Therefore, it is required to design such enhancement technique that do not compromise with the quality of the image. The optimization of the image extracts the characteristics of the image instead of restoring the degraded image. The improvement of the image involves the degraded image processing and the improvement of its visual aspect. A lot of research has been done to improve the image. Many research works have been done in this field. One among them is deep learning. Most of the existing contrast enhancement methods, adjust the tone curve to correct the contrast of an input image but doesn’t work efficiently due to limited amount of information contained in a single image. In this research, the CNN with edge adjustment is proposed. By applying CNN with Edge adjustment technique, the input low contrast images are capable to adapt according to high quality enhancement. The result analysis shows that the developed technique significantly advantages over existing methods

Are lip prints hereditary? A systematic review

Hereditary lip prints have been studied by several researchers. However, the literature shows no consensus among the scientific community regarding this topic. Therefore, the aim of this study was to conduct a systematic review to gather evidence to clarify whether the surface structure of lip prints is hereditary and, consequently, if a familial relationship between individuals can be established through the analysis of lip prints. The systematic review was performed following the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) guidelines. A bibliographic survey was conducted in PubMed, Scopus, and Web of Science databases, restricted to articles published between 2010 and 2020. Studies were selected according to eligibility criteria, and then the study data were collected. The risk of bias of each study was assessed and applied as additional inclusion or exclusion criteria. The results of the articles eligible for analysis were synthesized by a descriptive approach. In the seven included studies, methodological variations, including the definition of similarity, that contribute to the heterogeneity of results were identified. The data gathered allowed to conclude that there is no strong scientific evidence to support the hypothesis of the existence of heredity in the surface structure of lip prints, since it was not proven that similarities between parents and children occur systematically in all families.Open access funding provided by FCT|FCCN (b-on). The co-author Caldas IM was financed by the R&D Unit Centre for Functional Ecology-Science for People and the Planet (CFE), with reference UIDB/04004/2020, financed by FCT/MCTES through national funds (PIDDAC)

Living Knowledge

Diversity, especially manifested in language and knowledge, is a function of local goals, needs, competences, beliefs, culture, opinions and personal experience. The Living Knowledge project considers diversity as an asset rather than a problem. With the project, foundational ideas emerged from the synergic contribution of different disciplines, methodologies (with which many partners were previously unfamiliar) and technologies flowed in concrete diversity-aware applications such as the Future Predictor and the Media Content Analyser providing users with better structured information while coping with Web scale complexities. The key notions of diversity, fact, opinion and bias have been defined in relation to three methodologies: Media Content Analysis (MCA) which operates from a social sciences perspective; Multimodal Genre Analysis (MGA) which operates from a semiotic perspective and Facet Analysis (FA) which operates from a knowledge representation and organization perspective. A conceptual architecture that pulls all of them together has become the core of the tools for automatic extraction and the way they interact. In particular, the conceptual architecture has been implemented with the Media Content Analyser application. The scientific and technological results obtained are described in the following