PlaceRaider: Virtual Theft in Physical Spaces with Smartphones

As smartphones become more pervasive, they are increasingly targeted by malware. At the same time, each new generation of smartphone features increasingly powerful onboard sensor suites. A new strain of sensor malware has been developing that leverages these sensors to steal information from the physical environment (e.g., researchers have recently demonstrated how malware can listen for spoken credit card numbers through the microphone, or feel keystroke vibrations using the accelerometer). Yet the possibilities of what malware can see through a camera have been understudied. This paper introduces a novel visual malware called PlaceRaider, which allows remote attackers to engage in remote reconnaissance and what we call virtual theft. Through completely opportunistic use of the camera on the phone and other sensors, PlaceRaider constructs rich, three dimensional models of indoor environments. Remote burglars can thus download the physical space, study the environment carefully, and steal virtual objects from the environment (such as financial documents, information on computer monitors, and personally identifiable information). Through two human subject studies we demonstrate the effectiveness of using mobile devices as powerful surveillance and virtual theft platforms, and we suggest several possible defenses against visual malware

Linking recorded data with emotive and adaptive computing in an eHealth environment

Telecare, and particularly lifestyle monitoring, currently relies on the ability to detect and respond to changes in individual behaviour using data derived from sensors around the home. This means that a significant aspect of behaviour, that of an individuals emotional state, is not accounted for in reaching a conclusion as to the form of response required. The linked concepts of emotive and adaptive computing offer an opportunity to include information about emotional state and the paper considers how current developments in this area have the potential to be integrated within telecare and other areas of eHealth. In doing so, it looks at the development of and current state of the art of both emotive and adaptive computing, including its conceptual background, and places them into an overall eHealth context for application and development

Healthcare PANs: Personal Area Networks for trauma care and home care

The first hour following the trauma is of crucial importance in trauma care. The sooner treatment begins, the better the ultimate outcome for the patient. Generally the initial treatment is handled by paramedical personnel arriving at the site of the accident with an ambulance. There is evidence to show that if the expertise of the on-site paramedic team can be supported by immediate and continuous access to and communication with the expert medical team at the hospital, patient outcomes can be improved. After care also influences the ultimate recovery of the patient. After-treatment follow up often occurs in-hospital in spite of the fact that care at home can offer more advantages and can accelerate recovery. Based on emerging and future wireless communication technologies, in a previous paper [1] we presented an initial vision of two future healthcare settings, supported by applications which we call Virtual Trauma Team and Virtual Homecare Team. The Virtual Trauma Team application involves high quality wireless multimedia communications between ambulance paramedics and the hospital facilitated by paramedic Body Area Networks (BANs) [2] and an ambulance-based Vehicle Area Network (VAN). The VAN supports bi-directional streaming audio and video communication between the ambulance and the hospital even when moving at speed. The clinical motivation for Virtual Trauma Team is to increase survival rates in trauma care. The Virtual Homecare Team application enables homecare coordinated by home nursing services and supported by the patient's PAN which consists of a patient BAN in combination with an ambient intelligent home environment. The homecare PAN provides intelligent monitoring and support functions and the possibility to ad hoc network to the visiting health professionals’ own BANs as well as high quality multimedia communication links to remote members of the virtual team. The motivation for Virtual Homecare Team is to improve quality of life and independence for patients by supporting care at home; the economic motivation is to replace expensive hospital-based care with homecare by virtual teams using wireless technology to support the patient and the carers. In this paper we develop the vision further and focus in particular on the concepts of personal and body area networks

Radar and RGB-depth sensors for fall detection: a review

This paper reviews recent works in the literature on the use of systems based on radar and RGB-Depth (RGB-D) sensors for fall detection, and discusses outstanding research challenges and trends related to this research field. Systems to detect reliably fall events and promptly alert carers and first responders have gained significant interest in the past few years in order to address the societal issue of an increasing number of elderly people living alone, with the associated risk of them falling and the consequences in terms of health treatments, reduced well-being, and costs. The interest in radar and RGB-D sensors is related to their capability to enable contactless and non-intrusive monitoring, which is an advantage for practical deployment and users’ acceptance and compliance, compared with other sensor technologies, such as video-cameras, or wearables. Furthermore, the possibility of combining and fusing information from The heterogeneous types of sensors is expected to improve the overall performance of practical fall detection systems. Researchers from different fields can benefit from multidisciplinary knowledge and awareness of the latest developments in radar and RGB-D sensors that this paper is discussing