Biometrics-as-a-Service: A Framework to Promote Innovative Biometric Recognition in the Cloud

Biometric recognition, or simply biometrics, is the use of biological attributes such as face, fingerprints or iris in order to recognize an individual in an automated manner. A key application of biometrics is authentication; i.e., using said biological attributes to provide access by verifying the claimed identity of an individual. This paper presents a framework for Biometrics-as-a-Service (BaaS) that performs biometric matching operations in the cloud, while relying on simple and ubiquitous consumer devices such as smartphones. Further, the framework promotes innovation by providing interfaces for a plurality of software developers to upload their matching algorithms to the cloud. When a biometric authentication request is submitted, the system uses a criteria to automatically select an appropriate matching algorithm. Every time a particular algorithm is selected, the corresponding developer is rendered a micropayment. This creates an innovative and competitive ecosystem that benefits both software developers and the consumers. As a case study, we have implemented the following: (a) an ocular recognition system using a mobile web interface providing user access to a biometric authentication service, and (b) a Linux-based virtual machine environment used by software developers for algorithm development and submission

Audio-Visual Speaker Identification using the CUAVE Database

The freely available nature of the CUAVE database allows it to provide a valuable platform to form benchmarks and compare research. This paper shows that the CUAVE database can successfully be used to test speaker identifications systems, with performance comparable to existing systems implemented on other databases. Additionally, this research shows that the optimal configuration for decisionfusion of an audio-visual speaker identification system relies heavily on the video modality in all but clean speech conditions

Keystroke dynamics as a biometric

Modern computer systems rely heavily on methods of authentication and identity verification to protect sensitive data. One of the most robust protective techniques involves adding a layer of biometric analysis to other security mechanisms, as a means of establishing the identity of an individual beyond reasonable doubt. In the search for a biometric technique which is both low-cost and transparent to the end user, researchers have considered analysing the typing patterns of keyboard users to determine their characteristic timing signatures.Previous research into keystroke analysis has either required fixed performance of known keyboard input or relied on artificial tests involving the improvisation of a block of text for analysis. I is proposed that this is insufficient to determine the nature of unconstrained typing in a live computing environment. In an attempt to assess the utility of typing analysis for improving intrusion detection on computer systems, we present the notion of ‘genuinely free text’ (GFT). Through the course of this thesis, we discuss the nature of GFT and attempt to address whether it is feasible to produce a lightweight software platform for monitoring GFT keystroke biometrics, while protecting the privacy of users.The thesis documents in depth the design, development and deployment of the multigraph-based BAKER software platform, a system for collecting statistical GFT data from live environments. This software platform has enabled the collection of an extensive set of keystroke biometric data for a group of participating computer users, the analysis of which we also present here. Several supervised learning techniques were used to demonstrate that the richness of keystroke information gathered from BAKER is indeed sufficient to recommend multigraph keystroke analysis, as a means of augmenting computer security. In addition, we present a discussion of the feasibility of applying data obtained from GFT profiles in circumventing traditional static and free text analysis biometrics

Know Thy Toucher

Most of current academic and commercial surface computing systems are capable of multitouch detection and hence allow simultaneous input from multiple users. Although there are so far only few applications in this area which rely on identifying the user, we believe that the association of touches to users will become an essential feature of surface computing as applications mature, new application areas emerge, and the enabling technology is readily available. As the capacitive technology used in present user identification enabled tabletops is limited with respect to the supported number of users and screen size, we outline a user identification enabled tabletop concept based on computer vision and biometric hand shape information, and introduce the prototype system we built to further investigate this concept. In a preliminary consideration, we derive concepts for identifying users by examining what new possibilities are enabled and by introducing different scopes of identification

The individual and the system : Assessing the stability of the output of a semi-automatic forensic voice comparison system

Semi-automatic systems based on traditional linguistic-phonetic features are increasingly being used for forensic voice comparison (FVC) casework. In this paper, we examine the stability of the output of a semi-automatic system, based on the long-term formant distributions (LTFDs) of F1, F2, and F3, as the channel quality of the input recordings decreases. Cross-validated, calibrated GMM-UBM log likelihood-ratios (LLRs) were computed for 97 Standard Southern British English speakers under four conditions. In each condition the same speech material was used, but the technical properties of the recordings changed (high quality studio recording, landline telephone recording, high bit-rate GSM mobile telephone recording and low bit-rate GSM mobile telephone recording). Equal error rate (EER) and the log LR cost function (Cllr) were compared across conditions. System validity was found to decrease with poorer technical quality, with the largest differences in EER (21.66%) and Cllr (0.46) found between the studio and the low bit-rate GSM conditions. However, importantly, performance for individual speakers was affected differently by channel quality. Speakers that produced stronger evidence overall were found to be more variable. Mean F3 was also found to be a predictor of LLR variability, however no effects were found based on speakers’ voice quality profiles

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

A Regulatory Model for Context-Aware Abstract Framework

Proceedings of: 23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2010, Cordoba, Spain, June 1-4, 2010.This paper presents a general framework to define a context aware application and analyzes social guarantees to be considered to develop this kind of applications following legal assumptions as privacy, human rights, etc. We present a review of legal issues in biometric user identification where several legal aspects have been developed in European Union regulation and a general framework to define context aware applications. As main result, paper presents a legal framework to be taken into account in any context-based application to ensure a harmonious and coherent system for the protection of fundamental rights.This work was supported in part by Projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02-02/TEC, CAM CONTEXTS (S2009/TIC-1485) and DPS2008-07029- C02-02.Publicad

Strong authentication based on mobile application

The user authentication in online services has evolved over time from the old username and password-based approaches to current strong authentication methodologies. Especially, the smartphone app has become one of the most important forms to perform the authentication. This thesis describes various authentication methods used previously and discusses about possible factors that generated the demand for the current strong authentication approach. We present the concepts and architectures of mobile application based authentication systems. Furthermore, we take closer look into the security of the mobile application based authentication approach. Mobile apps have various attack vectors that need to be taken under consideration when designing an authentication system. Fortunately, various generic software protection mechanisms have been developed during the last decades. We discuss how these mechanisms can be utilized in mobile app environment and in the authentication context. The main idea of this thesis is to gather relevant information about the authentication history and to be able to build a view of strong authentication evolution. This history and the aspects of the evolution are used to state hypothesis about the future research and development. We predict that the authentication systems in the future may be based on a holistic view of the behavioral patterns and physical properties of the user. Machine learning may be used in the future to implement an autonomous authentication concept that enables users to be authenticated with minimal physical or cognitive effort

Mechatronics & the cloud

Conventionally, the engineering design process has assumed that the design team is able to exercise control over all elements of the design, either directly or indirectly in the case of sub-systems through their specifications. The introduction of Cyber-Physical Systems (CPS) and the Internet of Things (IoT) means that a design team’s ability to have control over all elements of a system is no longer the case, particularly as the actual system configuration may well be being dynamically reconfigured in real-time according to user (and vendor) context and need. Additionally, the integration of the Internet of Things with elements of Big Data means that information becomes a commodity to be autonomously traded by and between systems, again according to context and need, all of which has implications for the privacy of system users. The paper therefore considers the relationship between mechatronics and cloud-basedtechnologies in relation to issues such as the distribution of functionality and user privacy