In-ear EEG biometrics for feasible and readily collectable real-world person authentication

The use of EEG as a biometrics modality has been investigated for about a decade, however its feasibility in real-world applications is not yet conclusively established, mainly due to the issues with collectability and reproducibility. To this end, we propose a readily deployable EEG biometrics system based on a `one-fits-all' viscoelastic generic in-ear EEG sensor (collectability), which does not require skilled assistance or cumbersome preparation. Unlike most existing studies, we consider data recorded over multiple recording days and for multiple subjects (reproducibility) while, for rigour, the training and test segments are not taken from the same recording days. A robust approach is considered based on the resting state with eyes closed paradigm, the use of both parametric (autoregressive model) and non-parametric (spectral) features, and supported by simple and fast cosine distance, linear discriminant analysis and support vector machine classifiers. Both the verification and identification forensics scenarios are considered and the achieved results are on par with the studies based on impractical on-scalp recordings. Comprehensive analysis over a number of subjects, setups, and analysis features demonstrates the feasibility of the proposed ear-EEG biometrics, and its potential in resolving the critical collectability, robustness, and reproducibility issues associated with current EEG biometrics

One-Step, Three-Factor Passthought Authentication With Custom-Fit, In-Ear EEG

In-ear EEG offers a promising path toward usable, discreet brain-computer interfaces (BCIs) for both healthy individuals and persons with disabilities. To test the promise of this modality, we produced a brain-based authentication system using custom-fit EEG earpieces. In a sample of N = 7 participants, we demonstrated that our system has high accuracy, higher than prior work using non-custom earpieces. We demonstrated that both inherence and knowledge factors contribute to authentication accuracy, and performed a simulated attack to show our system's robustness against impersonation. From an authentication standpoint, our system provides three factors of authentication in a single step. From a usability standpoint, our system does not require a cumbersome, head-worn device

Sensing with Earables: A Systematic Literature Review and Taxonomy of Phenomena

Earables have emerged as a unique platform for ubiquitous computing by augmenting ear-worn devices with state-of-the-art sensing. This new platform has spurred a wealth of new research exploring what can be detected on a wearable, small form factor. As a sensing platform, the ears are less susceptible to motion artifacts and are located in close proximity to a number of important anatomical structures including the brain, blood vessels, and facial muscles which reveal a wealth of information. They can be easily reached by the hands and the ear canal itself is affected by mouth, face, and head movements. We have conducted a systematic literature review of 271 earable publications from the ACM and IEEE libraries. These were synthesized into an open-ended taxonomy of 47 different phenomena that can be sensed in, on, or around the ear. Through analysis, we identify 13 fundamental phenomena from which all other phenomena can be derived, and discuss the different sensors and sensing principles used to detect them. We comprehensively review the phenomena in four main areas of (i) physiological monitoring and health, (ii) movement and activity, (iii) interaction, and (iv) authentication and identification. This breadth highlights the potential that earables have to offer as a ubiquitous, general-purpose platform

Sensing with Earables: A Systematic Literature Review and Taxonomy of Phenomena

Earables have emerged as a unique platform for ubiquitous computing by augmenting ear-worn devices with state-of-the-art sensing. This new platform has spurred a wealth of new research exploring what can be detected on a wearable, small form factor. As a sensing platform, the ears are less susceptible to motion artifacts and are located in close proximity to a number of important anatomical structures including the brain, blood vessels, and facial muscles which reveal a wealth of information. They can be easily reached by the hands and the ear canal itself is affected by mouth, face, and head movements. We have conducted a systematic literature review of 271 earable publications from the ACM and IEEE libraries. These were synthesized into an open-ended taxonomy of 47 different phenomena that can be sensed in, on, or around the ear. Through analysis, we identify 13 fundamental phenomena from which all other phenomena can be derived, and discuss the different sensors and sensing principles used to detect them. We comprehensively review the phenomena in four main areas of (i) physiological monitoring and health, (ii) movement and activity, (iii) interaction, and (iv) authentication and identification. This breadth highlights the potential that earables have to offer as a ubiquitous, general-purpose platform

Non-Intrusive Subscriber Authentication for Next Generation Mobile Communication Systems

Merged with duplicate record 10026.1/753 on 14.03.2017 by CS (TIS)The last decade has witnessed massive growth in both the technological development, and the consumer adoption of mobile devices such as mobile handsets and PDAs. The recent introduction of wideband mobile networks has enabled the deployment of new services with access to traditionally well protected personal data, such as banking details or medical records. Secure user access to this data has however remained a function of the mobile device's authentication system, which is only protected from masquerade abuse by the traditional PIN, originally designed to protect against telephony abuse. This thesis presents novel research in relation to advanced subscriber authentication for mobile devices. The research began by assessing the threat of masquerade attacks on such devices by way of a survey of end users. This revealed that the current methods of mobile authentication remain extensively unused, leaving terminals highly vulnerable to masquerade attack. Further investigation revealed that, in the context of the more advanced wideband enabled services, users are receptive to many advanced authentication techniques and principles, including the discipline of biometrics which naturally lends itself to the area of advanced subscriber based authentication. To address the requirement for a more personal authentication capable of being applied in a continuous context, a novel non-intrusive biometric authentication technique was conceived, drawn from the discrete disciplines of biometrics and Auditory Evoked Responses. The technique forms a hybrid multi-modal biometric where variations in the behavioural stimulus of the human voice (due to the propagation effects of acoustic waves within the human head), are used to verify the identity o f a user. The resulting approach is known as the Head Authentication Technique (HAT). Evaluation of the HAT authentication process is realised in two stages. Firstly, the generic authentication procedures of registration and verification are automated within a prototype implementation. Secondly, a HAT demonstrator is used to evaluate the authentication process through a series of experimental trials involving a representative user community. The results from the trials confirm that multiple HAT samples from the same user exhibit a high degree of correlation, yet samples between users exhibit a high degree of discrepancy. Statistical analysis of the prototypes performance realised early system error rates of; FNMR = 6% and FMR = 0.025%. The results clearly demonstrate the authentication capabilities of this novel biometric approach and the contribution this new work can make to the protection of subscriber data in next generation mobile networks.Orange Personal Communication Services Lt

Earables: Wearable Computing on the Ears

Kopfhörer haben sich bei Verbrauchern durchgesetzt, da sie private Audiokanäle anbieten, zum Beispiel zum Hören von Musik, zum Anschauen der neuesten Filme während dem Pendeln oder zum freihändigen Telefonieren. Dank diesem eindeutigen primären Einsatzzweck haben sich Kopfhörer im Vergleich zu anderen Wearables, wie zum Beispiel Smartglasses, bereits stärker durchgesetzt. In den letzten Jahren hat sich eine neue Klasse von Wearables herausgebildet, die als "Earables" bezeichnet werden. Diese Geräte sind so konzipiert, dass sie in oder um die Ohren getragen werden können. Sie enthalten verschiedene Sensoren, um die Funktionalität von Kopfhörern zu erweitern. Die räumliche Nähe von Earables zu wichtigen anatomischen Strukturen des menschlichen Körpers bietet eine ausgezeichnete Plattform für die Erfassung einer Vielzahl von Eigenschaften, Prozessen und Aktivitäten. Auch wenn im Bereich der Earables-Forschung bereits einige Fortschritte erzielt wurden, wird deren Potenzial aktuell nicht vollständig abgeschöpft. Ziel dieser Dissertation ist es daher, neue Einblicke in die Möglichkeiten von Earables zu geben, indem fortschrittliche Sensorikansätze erforscht werden, welche die Erkennung von bisher unzugänglichen Phänomenen ermöglichen. Durch die Einführung von neuartiger Hardware und Algorithmik zielt diese Dissertation darauf ab, die Grenzen des Erreichbaren im Bereich Earables zu verschieben und diese letztlich als vielseitige Sensorplattform zur Erweiterung menschlicher Fähigkeiten zu etablieren. Um eine fundierte Grundlage für die Dissertation zu schaffen, synthetisiert die vorliegende Arbeit den Stand der Technik im Bereich der ohr-basierten Sensorik und stellt eine einzigartig umfassende Taxonomie auf der Basis von 271 relevanten Publikationen vor. Durch die Verbindung von Low-Level-Sensor-Prinzipien mit Higher-Level-Phänomenen werden in der Dissertation anschließ-end Arbeiten aus verschiedenen Bereichen zusammengefasst, darunter (i) physiologische Überwachung und Gesundheit, (ii) Bewegung und Aktivität, (iii) Interaktion und (iv) Authentifizierung und Identifizierung. Diese Dissertation baut auf der bestehenden Forschung im Bereich der physiologischen Überwachung und Gesundheit mit Hilfe von Earables auf und stellt fortschrittliche Algorithmen, statistische Auswertungen und empirische Studien vor, um die Machbarkeit der Messung der Atemfrequenz und der Erkennung von Episoden erhöhter Hustenfrequenz durch den Einsatz von In-Ear-Beschleunigungsmessern und Gyroskopen zu demonstrieren. Diese neuartigen Sensorfunktionen unterstreichen das Potenzial von Earables, einen gesünderen Lebensstil zu fördern und eine proaktive Gesundheitsversorgung zu ermöglichen. Darüber hinaus wird in dieser Dissertation ein innovativer Eye-Tracking-Ansatz namens "earEOG" vorgestellt, welcher Aktivitätserkennung erleichtern soll. Durch die systematische Auswertung von Elektrodenpotentialen, die um die Ohren herum mittels eines modifizierten Kopfhörers gemessen werden, eröffnet diese Dissertation einen neuen Weg zur Messung der Blickrichtung. Dabei ist das Verfahren weniger aufdringlich und komfortabler als bisherige Ansätze. Darüber hinaus wird ein Regressionsmodell eingeführt, um absolute Änderungen des Blickwinkels auf der Grundlage von earEOG vorherzusagen. Diese Entwicklung eröffnet neue Möglichkeiten für Forschung, welche sich nahtlos in das tägliche Leben integrieren lässt und tiefere Einblicke in das menschliche Verhalten ermöglicht. Weiterhin zeigt diese Arbeit, wie sich die einzigarte Bauform von Earables mit Sensorik kombinieren lässt, um neuartige Phänomene zu erkennen. Um die Interaktionsmöglichkeiten von Earables zu verbessern, wird in dieser Dissertation eine diskrete Eingabetechnik namens "EarRumble" vorgestellt, die auf der freiwilligen Kontrolle des Tensor Tympani Muskels im Mittelohr beruht. Die Dissertation bietet Einblicke in die Verbreitung, die Benutzerfreundlichkeit und den Komfort von EarRumble, zusammen mit praktischen Anwendungen in zwei realen Szenarien. Der EarRumble-Ansatz erweitert das Ohr von einem rein rezeptiven Organ zu einem Organ, das nicht nur Signale empfangen, sondern auch Ausgangssignale erzeugen kann. Im Wesentlichen wird das Ohr als zusätzliches interaktives Medium eingesetzt, welches eine freihändige und augenfreie Kommunikation zwischen Mensch und Maschine ermöglicht. EarRumble stellt eine Interaktionstechnik vor, die von den Nutzern als "magisch und fast telepathisch" beschrieben wird, und zeigt ein erhebliches ungenutztes Potenzial im Bereich der Earables auf. Aufbauend auf den vorhergehenden Ergebnissen der verschiedenen Anwendungsbereiche und Forschungserkenntnisse mündet die Dissertation in einer offenen Hard- und Software-Plattform für Earables namens "OpenEarable". OpenEarable umfasst eine Reihe fortschrittlicher Sensorfunktionen, die für verschiedene ohrbasierte Forschungsanwendungen geeignet sind, und ist gleichzeitig einfach herzustellen. Hierdurch werden die Einstiegshürden in die ohrbasierte Sensorforschung gesenkt und OpenEarable trägt somit dazu bei, das gesamte Potenzial von Earables auszuschöpfen. Darüber hinaus trägt die Dissertation grundlegenden Designrichtlinien und Referenzarchitekturen für Earables bei. Durch diese Forschung schließt die Dissertation die Lücke zwischen der Grundlagenforschung zu ohrbasierten Sensoren und deren praktischem Einsatz in realen Szenarien. Zusammenfassend liefert die Dissertation neue Nutzungsszenarien, Algorithmen, Hardware-Prototypen, statistische Auswertungen, empirische Studien und Designrichtlinien, um das Feld des Earable Computing voranzutreiben. Darüber hinaus erweitert diese Dissertation den traditionellen Anwendungsbereich von Kopfhörern, indem sie die auf Audio fokussierten Geräte zu einer Plattform erweitert, welche eine Vielzahl fortschrittlicher Sensorfähigkeiten bietet, um Eigenschaften, Prozesse und Aktivitäten zu erfassen. Diese Neuausrichtung ermöglicht es Earables sich als bedeutende Wearable Kategorie zu etablieren, und die Vision von Earables als eine vielseitige Sensorenplattform zur Erweiterung der menschlichen Fähigkeiten wird somit zunehmend realer

Review of Networking and Tangible Security Techniques for Domestic IoT Devices and Initial Ideas

The number of connected devices including Internet of Things (IoTs) on the Internet is growing fast. According to recent Gartner research, the estimated number of IoT devices is 5.8 billion in 2020 (Gartner, 2019). The countries that are leading the way to IoT deployment include North America, Western Europe and China (Kandaswamy and Furlonger, 2018). By 2024, the number of Machine-2-Machine (M2M) connections between these devices are expected to reach 27 billion in 2024 (Kandaswamy and Furlonger, 2018). This growth in M2M connectivity is expected to result from wide range of application areas such as smart cities, smart infrastructure, smart energy among many others (Hassija et al., 2019).This wide spread of IoTs has sparked significant research interest to understand various implications (Airehrour et al., 2016; Neshenko et al., 2019; Hassija et al., 2019). IoTs enable the integration between many objects in our daily life (Aazam et al., 2016; Alaba et al., 2017) such as sensors, objects, wearable devices and other types of machines. IoT devices are capable of communicating directly with one another and sharing data without direct human intervention (Crabtree et al., 2018). These “things” could be any traditional objects such as home appliance (e.g. microwave, fridge) or tiny sensor (e.g. humidity or health sensors). The devices are capable of constant collections of various sensitive and personal data about many aspect of our lives due to its pervasive deployment (Ren et al., 2019).This paper provides an overview of the literature relating to securing IoT with an emphasis on usability from a user perspective as well as approaches to securing access to these devices over the Internet. Although IoT deployment occurs in various settings, i.e. industrial IoT deployment, we mainly focus in this paper on private residential home deployment (i.e. consumer IoTs). We assume that in such settings, users are mostly not experts in security IoT or the underlying networking principles.This paper is organized as follows: section II discusses various protocols and networking security tools (e.g. firewall and Virtual Private Network (VPN)). Section II-D discusses various approaches to simplify cyber-security by using user-centred approaches. In section III, we present a number of existing including enterprise-grade solutions that could be adopted to secure remote access to IoT devices in domestic settings

Exploration of small enrollment speaker verification on handheld devices

Thesis (M. Eng. and S.B.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.Includes bibliographical references (p. 77-78).This thesis explores the problem of robust speaker verification for handheld devices under the context of extremely limited training data. Although speaker verification technology is an area of great promise for security applications, the implementation of such a system on handheld devices presents its own unique challenges arising from the highly mobile nature of the devices. This work first independently analyzes the impact of a number of key factors, such as speech features, basic modeling techniques, as well as highly variable environmental/microphone conditions on speaker verification accuracy. We then present and evaluate methods for improving speaker verification robustness. In particular, we focus on normalization techniques, such as handset normalization (H-norm), zero normalization (Z-norm) as well as model training methodologies (multistyle training) to minimize the detrimental impact of highly variable environment and microphone conditions on speaker verification robustness.by Ram H. Woo.M.Eng.and S.B