A fast and accurate energy source emulator for wireless sensor networks

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Sophisticated Batteryless Sensing

Wireless embedded sensing systems have revolutionized scientific, industrial, and consumer applications. Sensors have become a fixture in our daily lives, as well as the scientific and industrial communities by allowing continuous monitoring of people, wildlife, plants, buildings, roads and highways, pipelines, and countless other objects. Recently a new vision for sensing has emerged---known as the Internet-of-Things (IoT)---where trillions of devices invisibly sense, coordinate, and communicate to support our life and well being. However, the sheer scale of the IoT has presented serious problems for current sensing technologies---mainly, the unsustainable maintenance, ecological, and economic costs of recycling or disposing of trillions of batteries. This energy storage bottleneck has prevented massive deployments of tiny sensing devices at the edge of the IoT. This dissertation explores an alternative---leave the batteries behind, and harvest the energy required for sensing tasks from the environment the device is embedded in. These sensors can be made cheaper, smaller, and will last decades longer than their battery powered counterparts, making them a perfect fit for the requirements of the IoT. These sensors can be deployed where battery powered sensors cannot---embedded in concrete, shot into space, or even implanted in animals and people. However, these batteryless sensors may lose power at any point, with no warning, for unpredictable lengths of time. Programming, profiling, debugging, and building applications with these devices pose significant challenges. First, batteryless devices operate in unpredictable environments, where voltages vary and power failures can occur at any time---often devices are in failure for hours. Second, a device\u27s behavior effects the amount of energy they can harvest---meaning small changes in tasks can drastically change harvester efficiency. Third, the programming interfaces of batteryless devices are ill-defined and non- intuitive; most developers have trouble anticipating the problems inherent with an intermittent power supply. Finally, the lack of community, and a standard usable hardware platform have reduced the resources and prototyping ability of the developer. In this dissertation we present solutions to these challenges in the form of a tool for repeatable and realistic experimentation called Ekho, a reconfigurable hardware platform named Flicker, and a language and runtime for timely execution of intermittent programs called Mayfly

Design and validation of a scalable Digital Wireless Channel Emulator using an FPGA computing cluster

A Digital Wireless Channel Emulator (DWCE) is a system that is capable of emulating the RF environment for a group of wireless devices. The use of digital wireless channel emulators with networking radios is hampered by the inability to efficiently scale a DWCE to a large number of nodes. If such a large scale digital wireless channel emulator were to exist, a significant amount of time and money could be saved by testing networking radios in a laboratory before running lengthy and costly field tests. By utilizing the repeatability of a laboratory environment it will be possible to investigate and solve issues more quickly and efficiently. This will enable the performance of the radios to be known with a high degree of certainty before they are brought to the field. This dissertation investigates the use of an FPGA cluster configured as a distributed system to provide the computational and network structure to scale a DWCE to support 1250 or more wireless devices. This number of wireless devices is approximately two orders of magnitude larger than any other documented system. In this dissertation, the term ”scale” used for a DWCE is defined as an increase of three key factors: number of wireless devices, signal bandwidth emulated, and the fidelity of the emulation. It is possible to make tradeoffs and reduce any one of these to increase the other two. This dissertation shows a DWCE that can increase all of these factors in an efficient manner and thoroughly investigates the fidelity of the emulation it produces

A Study of Fidelity Level and Task/Non-Task Based Testing Scenarios on the Effectiveness of Usability Testing

Advances in usability are directing developers towards creating a better and all around friendlier environment for users. Unlike when buying a physical product where you purchase it first and then experience its usability, web site usability is immediately present. So, if a site doesn\u27t meet our needs, we as users, are quick to look elsewhere. Some research has suggested that fidelity makes no significant impact on users\u27 ability to locate errors or problems in a web site. This paper is intends to investigate the interaction between fidelity and task vs. non-task user testing with regards to the types of problems experienced by users. The goal is to identify the most efficient types of user testing. User testing is conventionally designed to emulate typical user situations and tasks. However the goal of testing is to find all possible problems with the interface\u27s design and correct or improve them. Asking users to perform typical tasks may not uncover all of these problems. Asking users to perform a non-task or browse the interface may provide additional information. And the interaction between fidelity and task should suggest that both types of tasks are needed at varying degrees of fidelity to ensure a quality user interface

Honeypots in the age of universal attacks and the Internet of Things

Today's Internet connects billions of physical devices. These devices are often immature and insecure, and share common vulnerabilities. The predominant form of attacks relies on recent advances in Internet-wide scanning and device discovery. The speed at which (vulnerable) devices can be discovered, and the device monoculture, mean that a single exploit, potentially trivial, can affect millions of devices across brands and continents. In an attempt to detect and profile the growing threat of autonomous and Internet-scale attacks against the Internet of Things, we revisit honeypots, resources that appear to be legitimate systems. We show that this endeavour was previously limited by a fundamentally flawed generation of honeypots and associated misconceptions. We show with two one-year-long studies that the display of warning messages has no deterrent effect in an attacked computer system. Previous research assumed that they would measure individual behaviour, but we find that the number of human attackers is orders of magnitude lower than previously assumed. Turning to the current generation of low- and medium-interaction honeypots, we demonstrate that their architecture is fatally flawed. The use of off-the-shelf libraries to provide the transport layer means that the protocols are implemented subtly differently from the systems being impersonated. We developed a generic technique which can find any such honeypot at Internet scale with just one packet for an established TCP connection. We then applied our technique and conducted several Internet-wide scans over a one-year period. By logging in to two SSH honeypots and sending specific commands, we not only revealed their configuration and patch status, but also found that many of them were not up to date. As we were the first to knowingly authenticate to honeypots, we provide a detailed legal analysis and an extended ethical justification for our research to show why we did not infringe computer-misuse laws. Lastly, we present honware, a honeypot framework for rapid implementation and deployment of high-interaction honeypots. Honware automatically processes a standard firmware image and can emulate a wide range of devices without any access to the manufacturers' hardware. We believe that honware is a major contribution towards re-balancing the economics of attackers and defenders by reducing the period in which attackers can exploit vulnerabilities at Internet scale in a world of ubiquitous networked `things'.Premium Research Studentship, Department of Computer Science and Technology, University of Cambridg

Pinching sweaters on your phone – iShoogle : multi-gesture touchscreen fabric simulator using natural on-fabric gestures to communicate textile qualities

The inability to touch fabrics online frustrates consumers, who are used to evaluating physical textiles by engaging in complex, natural gestural interactions. When customers interact with physical fabrics, they combine cross-modal information about the fabric's look, sound and handle to build an impression of its physical qualities. But whenever an interaction with a fabric is limited (i.e. when watching clothes online) there is a perceptual gap between the fabric qualities perceived digitally and the actual fabric qualities that a person would perceive when interacting with the physical fabric. The goal of this thesis was to create a fabric simulator that minimized this perceptual gap, enabling accurate perception of the qualities of fabrics presented digitally. We designed iShoogle, a multi-gesture touch-screen sound-enabled fabric simulator that aimed to create an accurate representation of fabric qualities without the need for touching the physical fabric swatch. iShoogle uses on-screen gestures (inspired by natural on-fabric movements e.g. Crunching) to control pre-recorded videos and audio of fabrics being deformed (e.g. being Crunched). iShoogle creates an illusion of direct video manipulation and also direct manipulation of the displayed fabric. This thesis describes the results of nine studies leading towards the development and evaluation of iShoogle. In the first three studies, we combined expert and non-expert textile-descriptive words and grouped them into eight dimensions labelled with terms Crisp, Hard, Soft, Textured, Flexible, Furry, Rough and Smooth. These terms were used to rate fabric qualities throughout the thesis. We observed natural on-fabric gestures during a fabric handling study (Study 4) and used the results to design iShoogle's on-screen gestures. In Study 5 we examined iShoogle's performance and speed in a fabric handling task and in Study 6 we investigated users' preferences for sound playback interactivity. iShoogle's accuracy was then evaluated in the last three studies by comparing participants’ ratings of textile qualities when using iShoogle with ratings produced when handling physical swatches. We also described the recording and processing techniques for the video and audio content that iShoogle used. Finally, we described the iShoogle iPhone app that was released to the general public. Our evaluation studies showed that iShoogle significantly improved the accuracy of fabric perception in at least some cases. Further research could investigate which fabric qualities and which fabrics are particularly suited to be represented with iShoogle