A smart environment for biometric capture

The development of large scale biometric systems require experiments to be performed on large amounts of data. Existing capture systems are designed for fixed experiments and are not easily scalable. In this scenario even the addition of extra data is difficult. We developed a prototype biometric tunnel for the capture of non-contact biometrics. It is self contained and autonomous. Such a configuration is ideal for building access or deployment in secure environments. The tunnel captures cropped images of the subject's face and performs a 3D reconstruction of the person's motion which is used to extract gait information. Interaction between the various parts of the system is performed via the use of an agent framework. The design of this system is a trade-off between parallel and serial processing due to various hardware bottlenecks. When tested on a small population the extracted features have been shown to be potent for recognition. We currently achieve a moderate throughput of approximate 15 subjects an hour and hope to improve this in the future as the prototype becomes more complete

A Multimodal Technique for an Embedded Fingerprint Recognizer in Mobile Payment Systems

The development and the diffusion of distributed systems, directly connected to recent communication technologies, move people towards the era of mobile and ubiquitous systems. Distributed systems make merchant-customer relationships closer and more flexible, using reliable e-commerce technologies. These systems and environments need many distributed access points, for the creation and management of secure identities and for the secure recognition of users. Traditionally, these access points can be made possible by a software system with a main central server. This work proposes the study and implementation of a multimodal technique, based on biometric information, for identity management and personal ubiquitous authentication. The multimodal technique uses both fingerprint micro features (minutiae) and fingerprint macro features (singularity points) for robust user authentication. To strengthen the security level of electronic payment systems, an embedded hardware prototype has been also created: acting as self-contained sensors, it performs the entire authentication process on the same device, so that all critical information (e.g. biometric data, account transactions and cryptographic keys), are managed and stored inside the sensor, without any data transmission. The sensor has been prototyped using the Celoxica RC203E board, achieving fast execution time, low working frequency, and good recognition performance

Face Liveness Detection for Biometric Antispoofing Applications using Color Texture and Distortion Analysis Features

Face recognition is a widely used biometric approach. Face recognition technology has developed rapidly in recent years and it is more direct, user friendly and convenient compared to other methods. But face recognition systems are vulnerable to spoof attacks made by non-real faces. It is an easy way to spoof face recognition systems by facial pictures such as portrait photographs. A secure system needs Liveness detection in order to guard against such spoofing. In this work, face liveness detection approaches are categorized based on the various types techniques used for liveness detection. This categorization helps understanding different spoof attacks scenarios and their relation to the developed solutions. A review of the latest works regarding face liveness detection works is presented. The main aim is to provide a simple path for the future development of novel and more secured face liveness detection approach

Development of a typing behaviour recognition mechanism on Android

This paper proposes a biometric authentication system which use password based and behavioural traits (typing behaviours) authentication technology to establish user’s identity on a mobile phone. The proposed system can work on the latest smart phone platform. It uses mobile devices to capture user’s keystroke data and transmit it to web server. The authentication engine will establish if a user is genuine or fraudulent. In addition, a multiplier of the standard deviation “α” has been defined which aims to achieve the balance between security and usability. Experimental results indicate that the developed authentication system is highly reliable and very secure with an equal error rate is below 7.5%

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

Homomorphic Encryption for Speaker Recognition: Protection of Biometric Templates and Vendor Model Parameters

Data privacy is crucial when dealing with biometric data. Accounting for the latest European data privacy regulation and payment service directive, biometric template protection is essential for any commercial application. Ensuring unlinkability across biometric service operators, irreversibility of leaked encrypted templates, and renewability of e.g., voice models following the i-vector paradigm, biometric voice-based systems are prepared for the latest EU data privacy legislation. Employing Paillier cryptosystems, Euclidean and cosine comparators are known to ensure data privacy demands, without loss of discrimination nor calibration performance. Bridging gaps from template protection to speaker recognition, two architectures are proposed for the two-covariance comparator, serving as a generative model in this study. The first architecture preserves privacy of biometric data capture subjects. In the second architecture, model parameters of the comparator are encrypted as well, such that biometric service providers can supply the same comparison modules employing different key pairs to multiple biometric service operators. An experimental proof-of-concept and complexity analysis is carried out on the data from the 2013-2014 NIST i-vector machine learning challenge

Phishing – the threat of internet banking

The attractiveness of Internet banking, the dynamics and the integration with e-business is still growing. The current use of electronic banking is defined by cyberspace and abused in the form of cyber terrorism as well. Therefore it is in the interest of all banks to focus on minimizing the real attacks. This article analyzes and compares the current possibilities against so-called phishing and identifies the area of the safe use of Internet banking in terms of the current potential threats in this area

Biometric Boom: How the Private Sector Commodifies Human Characteristics

Biometric technology has become an increasingly common part of daily life. Although biometrics have been used for decades, recent ad- vances and new uses have made the technology more prevalent, particu- larly in the private sector. This Note examines how widespread use of biometrics by the private sector is commodifying human characteristics. As the use of biometrics has become more extensive, it exacerbates and exposes individuals and industry to a number of risks and problems asso- ciated with biometrics. Despite public belief, biometric systems may be bypassed, hacked, or even fail. The more a characteristic is utilized, the less value it will hold for security purposes. Once compromised, a biome- tric cannot be replaced as would a password or other security device. This Note argues that there are strong justifications for a legal struc- ture that builds hurdles to slow the adoption of biometrics in the private sector. By examining the law and economics and personality theories of commodification, this Note identifies market failure and potential harm to personhood due to biometrics. The competing theories justify a reform to protect human characteristics from commodification. This Note presents a set of principles and tools based on defaults, disclosures, incen- tives, and taxation to discourage use of biometrics, buying time to streng- then the technology, educate the public, and establish legal safeguards for when the technology is compromised or fails