Device management of heterogeneous Bluetooth Low Energy devices

With the ever-growing adoption of smart, peripheral consumer devices, users enter a world where they can monitor their health and every day activities. As such, the advent of smart homes allows for the interconnectedness of all personal devices to be available on a unified platform. The efforts to unite all device management under a single banner has proven to be a difficult task, both in academia, and in consumer technologies. As mobility and limited power became the core of everyday computing, previous device management architectures have shown to be resource intensive and inapplicable to today's usage scenarios. This Master's Thesis presents a novel device architecture which enables efficient communication between devices, optimizes for system health, and utilizes all computing ability within its reach. Additionally, to aid in device intercommunication, the Master's Thesis also outlines a novel passive synchronization technique for peripheral devices which reduces overall energy consumption spent on scanning for other nodes

Fully Integrated Biochip Platforms for Advanced Healthcare

Recent advances in microelectronics and biosensors are enabling developments of innovative biochips for advanced healthcare by providing fully integrated platforms for continuous monitoring of a large set of human disease biomarkers. Continuous monitoring of several human metabolites can be addressed by using fully integrated and minimally invasive devices located in the sub-cutis, typically in the peritoneal region. This extends the techniques of continuous monitoring of glucose currently being pursued with diabetic patients. However, several issues have to be considered in order to succeed in developing fully integrated and minimally invasive implantable devices. These innovative devices require a high-degree of integration, minimal invasive surgery, long-term biocompatibility, security and privacy in data transmission, high reliability, high reproducibility, high specificity, low detection limit and high sensitivity. Recent advances in the field have already proposed possible solutions for several of these issues. The aim of the present paper is to present a broad spectrum of recent results and to propose future directions of development in order to obtain fully implantable systems for the continuous monitoring of the human metabolism in advanced healthcare applications

Cryptographic transfer of sensor data from the Amulet to a smartphone

The authenticity, confidentiality, and integrity of data streams from wearable healthcare devices are critical to patients, researchers, physicians, and others who depend on this data to measure the effectiveness of treatment plans and clinical trials. Many forms of mHealth data are highly sensitive; in the hands of unintended parties such data may reveal indicators of a patient\u27s disorder, disability, or identity. Furthermore, if a malicious party tampers with the data, it can affect the diagnosis or treatment of patients, or the results of a research study. Although existing network protocols leverage encryption for confidentiality and integrity, network-level encryption does not provide end-to-end security from the device, through the smartphone and database, to downstream data consumers. In this thesis we provide a new open protocol that provides end-to-end authentication, confidentiality, and integrity for healthcare data in such a pipeline. We present and evaluate a prototype implementation to demonstrate this protocol\u27s feasibility on low-power wearable devices, and present a case for the system\u27s ability to meet critical security properties under a specific adversary model and trust assumptions

Health Participatory Sensing Networks for Mobile Device Public Health Data Collection and Intervention

The pervasive availability and increasingly sophisticated functionalities of smartphones and their connected external sensors or wearable devices can provide new data collection capabilities relevant to public health. Current research and commercial efforts have concentrated on sensor-based collection of health data for personal fitness and personal healthcare feedback purposes. However, to date there has not been a detailed investigation of how such smartphones and sensors can be utilized for public health data collection. Unlike most sensing applications, in the case of public health, capturing comprehensive and detailed data is not a necessity, as aggregate data alone is in many cases sufficient for public health purposes. As such, public health data has the characteristic of being capturable whilst still not infringing privacy, as the detailed data of individuals that may allow re-identification is not needed, but rather only aggregate, de-identified and non-unique data for an individual. These types of public health data collection provide the challenge of the need to be flexible enough to answer a range of public health queries, while ensuring the level of detail returned preserves privacy. Additionally, the distribution of public health data collection request and other information to the participants without identifying the individual is a core requirement. An additional requirement for health participatory sensing networks is the ability to perform public health interventions. As with data collection, this needs to be completed in a non-identifying and privacy preserving manner. This thesis proposes a solution to these challenges, whereby a form of query assurance provides private and secure distribution of data collection requests and public health interventions to participants. While an additional, privacy preserving threshold approach to local processing of data prior to submission is used to provide re-identification protection for the participant. The evaluation finds that with manageable overheads, minimal reduction in the detail of collected data and strict communication privacy; privacy and anonymity can be preserved. This is significant for the field of participatory health sensing as a major concern of participants is most often real or perceived privacy risks of contribution

Practical privacy enhancing technologies for mobile systems

Mobile computers and handheld devices can be used today to connect to services available on the Internet. One of the predominant technologies in this respect for wireless Internet connection is the IEEE 802.11 family of WLAN standards. In many countries, WLAN access can be considered ubiquitous; there is a hotspot available almost anywhere. Unfortunately, the convenience provided by wireless Internet access has many privacy tradeoffs that are not obvious to mobile computer users. In this thesis, we investigate the lack of privacy of mobile computer users, and propose practical enhancements to increase the privacy of these users. We show how explicit information related to the users' identity leaks on all layers of the protocol stack. Even before an IP address is configured, the mobile computer may have already leaked their affiliation and other details to the local network as the WLAN interface openly broadcasts the networks that the user has visited. Free services that require authentication or provide personalization, such as online social networks, instant messengers, or web stores, all leak the user's identity. All this information, and much more, is available to a local passive observer using a mobile computer. In addition to a systematic analysis of privacy leaks, we have proposed four complementary privacy protection mechanisms. The main design guidelines for the mechanisms have been deployability and the introduction of minimal changes to user experience. More specifically, we mitigate privacy problems introduced by the standard WLAN access point discovery by designing a privacy-preserving access-point discovery protocol, show how a mobility management protocol can be used to protect privacy, and how leaks on all layers of the stack can be reduced by network location awareness and protocol stack virtualization. These practical technologies can be used in designing a privacy-preserving mobile system or can be retrofitted to current systems

Internet of Things (IoT) Applications With Diverse Direct Communication Methods

Title from PDF of title page viewed August 28, 2017Dissertation advisor: Baek-Young ChoiVitaIncludes bibliographical references (pages 124-138)Thesis (Ph.D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2016Internet of Things (IoT) is a network of physical objects or things that are embedded with electronics, software, sensors, and network connectivity - which enable the object to collect and exchange data. Rapid proliferation of IoT is driving the intelligence in things used daily in homes, workplaces and industry. The IoT devices typically communicate via radio frequency (RF), such as WiFi and Bluetooth. In this dissertation we deeply analyze the various characteristics of different wireless communication methods in terms of range, energy-efficiency, and radiation pattern. We find that a well-established communication method might not be the most efficient, and other alternate communication methods with the desired properties for a particular application could exist. We exploit radically alternative, innovative, and complimentary wireless communication methods, including radio frequency, infrared (IR), and visible lights, through the IoT applications we have designed and built with those. We have developed various IoT applications which provide security and authentication, enable vehicular communications with smartphones or other smart devices, provide energy-efficient and accurate positioning to smart devices, and enable energy-efficient communications in Industrial Internet of Things (IIoT).Introduction -- Optical wireless authentication for SMART devices using an onboard ambient light sensor -- Smartphome based CAR2X-communication with wifi beacon stuffing for vulnerable road user safety -- Energy-efficient cooperative opportunistic positioning heterogeneous Smart devices -- Reducing and balancing energy consumption in Indistrial Internet of Things (IIoT) -- Optical wireless unlocking for Smart door locks using Smartphones -- Summary and future direction

Privacy-preserving controls for sharing mHealth data

Mobile devices allow people to collect and share health and health-related information with recipients such as health providers, family and friends, employers and insurance companies, to obtain health, emotional or financial benefits. People may consider certain health information sensitive and prefer to disclose only what is necessary. In this dissertation, we present our findings about factors that affect people’s sharing behavior, describe scenarios in which people may wish to collect and share their personal health-related information with others, but may be hesitant to disclose the information if necessary controls are not available to protect their privacy, and propose frameworks to provide the desired privacy controls. We introduce the concept of close encounters that allow users to share data with other people who may have been in spatio-temporal proximity. We developed two smartphone-based systems that leverage stationary sensors and beacons to determine whether users are in spatio-temporal proximity. The first system, ENACT, allows patients diagnosed with a contagious airborne disease to alert others retrospectively about their possible exposure to airborne virus. The second system, SPICE, allows users to collect sensor information, retrospectively, from others with whom they shared a close encounter. We present design and implementation of the two systems, analyse their security and privacy guarantees, and evaluate the systems on various performance metrics. Finally, we evaluate how Bluetooth beacons and Wi-Fi access points can be used in support of these systems for close encounters, and present our experiences and findings from a deployment study on Dartmouth campus

Design Patterns for Situated Visualization in Augmented Reality

Situated visualization has become an increasingly popular research area in the visualization community, fueled by advancements in augmented reality (AR) technology and immersive analytics. Visualizing data in spatial proximity to their physical referents affords new design opportunities and considerations not present in traditional visualization, which researchers are now beginning to explore. However, the AR research community has an extensive history of designing graphics that are displayed in highly physical contexts. In this work, we leverage the richness of AR research and apply it to situated visualization. We derive design patterns which summarize common approaches of visualizing data in situ. The design patterns are based on a survey of 293 papers published in the AR and visualization communities, as well as our own expertise. We discuss design dimensions that help to describe both our patterns and previous work in the literature. This discussion is accompanied by several guidelines which explain how to apply the patterns given the constraints imposed by the real world. We conclude by discussing future research directions that will help establish a complete understanding of the design of situated visualization, including the role of interactivity, tasks, and workflows.Comment: To appear in IEEE VIS 202

Proceedings of the 3rd IUI Workshop on Interacting with Smart Objects

These are the Proceedings of the 3rd IUI Workshop on Interacting with Smart Objects. Objects that we use in our everyday life are expanding their restricted interaction capabilities and provide functionalities that go far beyond their original functionality. They feature computing capabilities and are thus able to capture information, process and store it and interact with their environments, turning them into smart objects