On the security of consumer wearable devices in the Internet of Things

Miniaturization of computer hardware and the demand for network capable devices has resulted in the emergence of a new class of technology called wearable computing. Wearable devices have many purposes like lifestyle support, health monitoring, fitness monitoring, entertainment, industrial uses, and gaming. Wearable devices are hurriedly being marketed in an attempt to capture an emerging market. Owing to this, some devices do not adequately address the need for security. To enable virtualization and connectivity wearable devices sense and transmit data, therefore it is essential that the device, its data and the user are protected. In this paper the use of novel Integrated Circuit Metric (ICMetric) technology for the provision of security in wearable devices has been suggested. ICMetric technology uses the features of a device to generate an identification which is then used for the provision of cryptographic services. This paper explores how a device ICMetric can be generated by using the accelerometer and gyroscope sensor. Since wearable devices often operate in a group setting the work also focuses on generating a group identification which is then used to deliver services like authentication, confidentiality, secure admission and symmetric key generation. Experiment and simulation results prove that the scheme offers high levels of security without compromising on resource demands

Feasibility study of detecting surface electromyograms in severely obese patients

The aims of this study were to examine if surface EMG signals can be detected from the quadriceps femoris muscle of severely obese patients and to investigate if differences exist in quadriceps force and myoelectric manifestations of fatigue between obese patients and lean controls. Fourteen severely obese patients (body mass index, BMI, mean±SD: 44.9±6.3kg/m(2)) and fourteen healthy controls (BMI: 23.7±2.5kg/m(2)) were studied. The vastus medialis and lateralis of the dominant thigh were concurrently investigated during voluntary isometric contractions (10-s long at submaximal and maximal intensities and intermittent submaximal contractions until exhaustion) and sustained (120-s long) electrically elicited contractions. We found that the detection of surface EMG signals from the quadriceps is feasible also in severely obese subjects presenting increased thickness of the subcutaneous fat tissue. In addition, we confirmed and extended previous findings showing that the volume conductor properties determine the amplitude and spectral features of the detected surface EMG signals: the lower the subcutaneous tissue thickness, the higher the amplitude and mean frequency estimates. Further, we found no differences in the mechanical and myoelectric manifestations of fatigue during intermittent voluntary and sustained electrically elicited contractions between obese patients and lean controls

Walking Through the Deep: Gait Analysis for User Authentication Through Deep Learning

Part 1: AuthenticationInternational audienceSeamless authentication is a desired feature which is becoming more and more relevant, due to the distribution of personal and wearable mobile devices. With seamless authentication, biometric features such as human gait, become a way to control authorized access on mobile devices, without actually requiring user interaction. However, this analysis is a challenging task, prone to errors, with the need to dynamic adapt to new conditions and requirements, brought by the dynamic change of biometric parameters. In this paper we present a novel deep-learning based framework for gait-based authentication. The paper presents an in depth study of the building and training of a Recurrent Convolutional Neural Network with a real dataset based on gait reading performed through five body sensors. We introduce methodologies to further increase the classification accuracy based on data augmentation and selective filtering. Finally we will present a complete experimental evaluation performed on more than 150 different identities

A Survey of Machine Learning Algorithms and Their Application in Information Security

In this survey, we touch on the breadth of applications of machine learning to problems in information security. A wide variety of machine learning techniques are introduced, and a sample of the applications of each to security-related problems is briefly discussed