Biblio

To prevent users' privacy from leakage, more and more mobile devices employ biometric-based authentication approaches, such as fingerprint, face recognition, voiceprint authentications, etc., to enhance the privacy protection. However, these approaches are vulnerable to replay attacks. Although state-of-art solutions utilize liveness verification to combat the attacks, existing approaches are sensitive to ambient environments, such as ambient lights and surrounding audible noises. Towards this end, we explore liveness verification of user authentication leveraging users' lip movements, which are robust to noisy environments. In this paper, we propose a lip reading-based user authentication system, LipPass, which extracts unique behavioral characteristics of users' speaking lips leveraging build-in audio devices on smartphones for user authentication. We first investigate Doppler profiles of acoustic signals caused by users' speaking lips, and find that there are unique lip movement patterns for different individuals. To characterize the lip movements, we propose a deep learning-based method to extract efficient features from Doppler profiles, and employ Support Vector Machine and Support Vector Domain Description to construct binary classifiers and spoofer detectors for user identification and spoofer detection, respectively. Afterwards, we develop a binary tree-based authentication approach to accurately identify each individual leveraging these binary classifiers and spoofer detectors with respect to registered users. Through extensive experiments involving 48 volunteers in four real environments, LipPass can achieve 90.21% accuracy in user identification and 93.1% accuracy in spoofer detection.

In this paper we discuss the Internet of Things (IoT) by exploring aspects which go beyond the proliferation of devices and information enabled by: the growth of the Internet, increased miniaturization, prolonged battery life and an IT literate user base. We highlight the role of feedback mechanisms and illustrate this with reference to implemented computer enabled factory control systems. As the technology has developed, the cost of computing has reduced drastically, programming interfaces have improved, sensors are simpler and more cost effective and high performance communications across a wide area are readily available. We illustrate this by considering an application based on the Raspberry Pi, which is a low cost, small, programmable and network capable computer based on a powerful ARM processor with a programmable I/O interface, which can provide access to sensors (and other devices). The prototype application running on this platform can sense the presence of human being, using inexpensive passive infrared detectors. This can be used to monitor the activity of vulnerable adults, logging the results to a central server using a domestic Internet solution over a Wireless LAN. Whilst this demonstrates the potential for the use of such control/monitoring systems, practical systems spanning thousands of sites will be more complex to deliver and will have more stringent data processing and management demands and security requirements. We will discuss these concepts in the context of delivery of a smart interconnected society.