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

Multi-Sensor Context-Awareness in Mobile Devices and Smart Artefacts

The use of context in mobile devices is receiving increasing attention in mobile and ubiquitous computing research. In this article we consider how to augment mobile devices with awareness of their environment and situation as context. Most work to date has been based on integration of generic context sensors, in particular for location and visual context. We propose a different approach based on integration of multiple diverse sensors for awareness of situational context that can not be inferred from location, and targeted at mobile device platforms that typically do not permit processing of visual context. We have investigated multi-sensor context-awareness in a series of projects, and report experience from development of a number of device prototypes. These include development of an awareness module for augmentation of a mobile phone, of the Mediacup exemplifying context-enabled everyday artifacts, and of the Smart-Its platform for aware mobile devices. The prototypes have been explored in various applications to validate the multi-sensor approach to awareness, and to develop new perspectives of how embedded context-awareness can be applied in mobile and ubiquitous computing

Emotion Recognition from Speech with Acoustic, Non-Linear and Wavelet-based Features Extracted in Different Acoustic Conditions

ABSTRACT: In the last years, there has a great progress in automatic speech recognition. The challenge now it is not only recognize the semantic content in the speech but also the called "paralinguistic" aspects of the speech, including the emotions, and the personality of the speaker. This research work aims in the development of a methodology for the automatic emotion recognition from speech signals in non-controlled noise conditions. For that purpose, different sets of acoustic, non-linear, and wavelet based features are used to characterize emotions in different databases created for such purpose

Harnessing AI for Speech Reconstruction using Multi-view Silent Video Feed

Speechreading or lipreading is the technique of understanding and getting phonetic features from a speaker's visual features such as movement of lips, face, teeth and tongue. It has a wide range of multimedia applications such as in surveillance, Internet telephony, and as an aid to a person with hearing impairments. However, most of the work in speechreading has been limited to text generation from silent videos. Recently, research has started venturing into generating (audio) speech from silent video sequences but there have been no developments thus far in dealing with divergent views and poses of a speaker. Thus although, we have multiple camera feeds for the speech of a user, but we have failed in using these multiple video feeds for dealing with the different poses. To this end, this paper presents the world's first ever multi-view speech reading and reconstruction system. This work encompasses the boundaries of multimedia research by putting forth a model which leverages silent video feeds from multiple cameras recording the same subject to generate intelligent speech for a speaker. Initial results confirm the usefulness of exploiting multiple camera views in building an efficient speech reading and reconstruction system. It further shows the optimal placement of cameras which would lead to the maximum intelligibility of speech. Next, it lays out various innovative applications for the proposed system focusing on its potential prodigious impact in not just security arena but in many other multimedia analytics problems.Comment: 2018 ACM Multimedia Conference (MM '18), October 22--26, 2018, Seoul, Republic of Kore

A Phone Learning Model for Enhancing Productivity of Visually Impaired Civil Servants

Phone-based learning in civil service is the use of voice technologies to deliver learning and capacity building training services to government employees. The Internet revolution and advancement in Information and Communications Technology (ICT) have given rise to online and remote staff training for the purpose of enhancing workers productivity. The need for civil servants in Nigeria to develop capacity that will enhance knowledge is a key requirement to having competitive advantage in the work place. Existing online learning platforms (such as web-based learning, mobile learning, etc) did not consider the plight of the visually impaired. These platforms provide graphical interfaces that require sight to access. The visually impaired civil servants require auditory access to functionalities that exist in learning management system on the Internet. Thus a gap exist between the able-bodied and visually impaired civil servants on accessibility to e-learning platform. The objective of this paper is to provide a personalized telephone learning model and a prototype application that will enhance the productivity of the visually impaired workers in Government establishments in Nigeria. The model was designed using Unified Modeling Language (UML) diagram. The prototype application was implemented and evaluated. With the proposed model and application, the visually and mobility impaired worker are able to participate in routine staff training and consequently enhances their productivity just like their able-bodied counterparts. The prototype application also serves as an alternative training platform for the able-bodied workers. Future research direction for this study will include biometric authentication of learners accessing the applicatio

A Phone Learning Model for Enhancing Productivity of Visually Impaired Civil Servants

Phone-based learning in civil service is the use of voice technologies to deliver learning and capacity building training services to government employees. The Internet revolution and advancement in Information and Communications Technology (ICT) have given rise to online and remote staff training for the purpose of enhancing workers productivity. The need for civil servants in Nigeria to develop capacity that will enhance knowledge is a key requirement to having competitive advantage in the work place. Existing online learning platforms (such as web-based learning, mobile learning, etc) did not consider the plight of the visually impaired. These platforms provide graphical interfaces that require sight to access. The visually impaired civil servants require auditory access to functionalities that exist in learning management system on the Internet. Thus a gap exist between the able-bodied and visually impaired civil servants on accessibility to e-learning platform. The objective of this paper is to provide a personalized telephone learning model and a prototype application that will enhance the productivity of the visually impaired workers in Government establishments in Nigeria. The model was designed using Unified Modeling Language (UML) diagram. The prototype application was implemented and evaluated. With the proposed model and application, the visually and mobility impaired worker are able to participate in routine staff training and consequently enhances their productivity just like their able-bodied counterparts. The prototype application also serves as an alternative training platform for the able-bodied workers. Future research direction for this study will include biometric authentication of learners accessing the applicatio