Towards Practical and Secure Channel Impulse Response-based Physical Layer Key Generation

Der derzeitige Trend hin zu “smarten” Geräten bringt eine Vielzahl an Internet-fähigen und verbundenen Geräten mit sich. Die entsprechende Kommunikation dieser Geräte muss zwangsläufig durch geeignete Maßnahmen abgesichert werden, um die datenschutz- und sicherheitsrelevanten Anforderungen an die übertragenen Informationen zu erfüllen. Jedoch zeigt die Vielzahl an sicherheitskritischen Vorfällen im Kontext von “smarten” Geräten und des Internets der Dinge auf, dass diese Absicherung der Kommunikation derzeit nur unzureichend umgesetzt wird. Die Ursachen hierfür sind vielfältig: so werden essentielle Sicherheitsmaßnahmen im Designprozess mitunter nicht berücksichtigt oder auf Grund von Preisdruck nicht realisiert. Darüber hinaus erschwert die Beschaffenheit der eingesetzten Geräte die Anwendung klassischer Sicherheitsverfahren. So werden in diesem Kontext vorrangig stark auf Anwendungsfälle zugeschnittene Lösungen realisiert, die auf Grund der verwendeten Hardware meist nur eingeschränkte Rechen- und Energieressourcen zur Verfügung haben. An dieser Stelle können die Ansätze und Lösungen der Sicherheit auf physikalischer Schicht (physical layer security, PLS) eine Alternative zu klassischer Kryptografie bieten. Im Kontext der drahtlosen Kommunikation können hier die Eigenschaften des Übertragungskanals zwischen zwei legitimen Kommunikationspartnern genutzt werden, um Sicherheitsprimitive zu implementieren und damit Sicherheitsziele zu realisieren. Konkret können etwa reziproke Kanaleigenschaften verwendet werden, um einen Vertrauensanker in Form eines geteilten, symmetrischen Geheimnisses zu generieren. Dieses Verfahren wird Schlüsselgenerierung basierend auf Kanalreziprozität (channel reciprocity based key generation, CRKG) genannt. Auf Grund der weitreichenden Verfügbarkeit wird dieses Verfahren meist mit Hilfe der Kanaleigenschaft des Empfangsstärkenindikators (received signal strength indicator, RSSI) realisiert. Dies hat jedoch den Nachteil, dass alle physikalischen Kanaleigenschaften auf einen einzigen Wert heruntergebrochen werden und somit ein Großteil der verfügbaren Informationen vernachlässigt wird. Dem gegenüber steht die Verwendung der vollständigen Kanalzustandsinformationen (channel state information, CSI). Aktuelle technische Entwicklungen ermöglichen es zunehmend, diese Informationen auch in Alltagsgeräten zur Verfügung zu stellen und somit für PLS weiterzuverwenden. In dieser Arbeit analysieren wir Fragestellungen, die sich aus einem Wechsel hin zu CSI als verwendetes Schlüsselmaterial ergeben. Konkret untersuchen wir CSI in Form von Ultrabreitband-Kanalimpulsantworten (channel impulse response, CIR). Für die Untersuchungen haben wir initial umfangreiche Messungen vorgenommen und damit analysiert, in wie weit die grundlegenden Annahmen von PLS und CRKG erfüllt sind und die CIRs sich grundsätzlich für die Schlüsselgenerierung eignen. Hier zeigen wir, dass die CIRs der legitimen Kommunikationspartner eine höhere Ähnlichkeit als die eines Angreifers aufzeigen und das somit ein Vorteil gegenüber diesem auf der physikalischen Schicht besteht, der für die Schlüsselgenerierung ausgenutzt werden kann. Basierend auf den Ergebnissen der initialen Untersuchung stellen wir dann grundlegende Verfahren vor, die notwendig sind, um die Ähnlichkeit der legitimen Messungen zu verbessern und somit die Schlüsselgenerierung zu ermöglichen. Konkret werden Verfahren vorgestellt, die den zeitlichen Versatz zwischen reziproken Messungen entfernen und somit die Ähnlichkeit erhöhen, sowie Verfahren, die das in den Messungen zwangsläufig vorhandene Rauschen entfernen. Gleichzeitig untersuchen wir, inwieweit die getroffenen fundamentalen Sicherheitsannahmen aus Sicht eines Angreifers erfüllt sind. Zu diesem Zweck präsentieren, implementieren und analysieren wir verschiedene praktische Angriffsmethoden. Diese Verfahren umfassen etwa Ansätze, bei denen mit Hilfe von deterministischen Kanalmodellen oder durch ray tracing versucht wird, die legitimen CIRs vorherzusagen. Weiterhin untersuchen wir Machine Learning Ansätze, die darauf abzielen, die legitimen CIRs direkt aus den Beobachtungen eines Angreifers zu inferieren. Besonders mit Hilfe des letzten Verfahrens kann hier gezeigt werden, dass große Teile der CIRs deterministisch vorhersagbar sind. Daraus leitet sich der Schluss ab, dass CIRs nicht ohne adäquate Vorverarbeitung als Eingabe für Sicherheitsprimitive verwendet werden sollten. Basierend auf diesen Erkenntnissen entwerfen und implementieren wir abschließend Verfahren, die resistent gegen die vorgestellten Angriffe sind. Die erste Lösung baut auf der Erkenntnis auf, dass die Angriffe aufgrund von vorhersehbaren Teilen innerhalb der CIRs möglich sind. Daher schlagen wir einen klassischen Vorverarbeitungsansatz vor, der diese deterministisch vorhersagbaren Teile entfernt und somit das Eingabematerial absichert. Wir implementieren und analysieren diese Lösung und zeigen ihre Effektivität sowie ihre Resistenz gegen die vorgeschlagenen Angriffe. In einer zweiten Lösung nutzen wir die Fähigkeiten des maschinellen Lernens, indem wir sie ebenfalls in das Systemdesign einbringen. Aufbauend auf ihrer starken Leistung bei der Mustererkennung entwickeln, implementieren und analysieren wir eine Lösung, die lernt, die zufälligen Teile aus den rohen CIRs zu extrahieren, durch die die Kanalreziprozität definiert wird, und alle anderen, deterministischen Teile verwirft. Damit ist nicht nur das Schlüsselmaterial gesichert, sondern gleichzeitig auch der Abgleich des Schlüsselmaterials, da Differenzen zwischen den legitimen Beobachtungen durch die Merkmalsextraktion effizient entfernt werden. Alle vorgestellten Lösungen verzichten komplett auf den Austausch von Informationen zwischen den legitimen Kommunikationspartnern, wodurch der damit verbundene Informationsabfluss sowie Energieverbrauch inhärent vermieden wird

Ultra Wideband

Ultra wideband (UWB) has advanced and merged as a technology, and many more people are aware of the potential for this exciting technology. The current UWB field is changing rapidly with new techniques and ideas where several issues are involved in developing the systems. Among UWB system design, the UWB RF transceiver and UWB antenna are the key components. Recently, a considerable amount of researches has been devoted to the development of the UWB RF transceiver and antenna for its enabling high data transmission rates and low power consumption. Our book attempts to present current and emerging trends in-research and development of UWB systems as well as future expectations

Detecting Vital Signs with Wearable Wireless Sensors

The emergence of wireless technologies and advancements in on-body sensor design can enable change in the conventional health-care system, replacing it with wearable health-care systems, centred on the individual. Wearable monitoring systems can provide continuous physiological data, as well as better information regarding the general health of individuals. Thus, such vital-sign monitoring systems will reduce health-care costs by disease prevention and enhance the quality of life with disease management. In this paper, recent progress in non-invasive monitoring technologies for chronic disease management is reviewed. In particular, devices and techniques for monitoring blood pressure, blood glucose levels, cardiac activity and respiratory activity are discussed; in addition, on-body propagation issues for multiple sensors are presented

Markerless Gait Classification Employing 3D IR-UWB Physiological Motion Sensing

Human gait refers to the propulsion achieved by the effort of human limbs, a reflex progression resulting from the rhythmic reciprocal bursts of flexor and extensor activity. Several quantitative models are followed by health professionals to diagnose gait abnormality. Marker-based gait quantification is considered a gold standard by the research and health communities. It reconstructs motion in 3D and provides parameters to measure gait. But, it is an expensive and intrusive technique, limited to soft tissue artefact, prone to incorrect marker positioning, and skin sensitivity problems. Hence, markerless, swiftly deployable, non-intrusive, camera-less prototypes would be a game changing possibility, and an example is proposed here. This paper illustrates a 3D gait motion analyser employing impulse radio ultra-wide band (IR-UWB) wireless technology. The prototype can measure 3D motion and determine quantitative parameters considering anatomical reference planes. Knee angles have been calculated from the gait by applying vector algebra. Simultaneously, the model has been corroborated with the popular markerless camera based 3D motion capturing system, the Kinect sensor. Bland and Altman (B&A) statistics has been applied to the proposed prototype and Kinect sensor results to verify the measurement agreement. Finally, the proposed prototype has been incorporated with popular supervised machine learning such as, k-nearest neighbour (kNN), support vector machine (SVM) and the deep learning technique deep neural multilayer perceptron (DMLP) network to automatically recognize gait abnormalities, with promising results presented

Deploying Wireless Sensor Devices in Intelligent Transportation System Applications

As future intelligent infrastructure will bring together and connect individuals, vehicles and infrastructure through wireless communications, it is critical that robust communication technologies are developed. Mobile wireless sensor networks are self-organising mobile networks where nodes exchange data without the need for an underlying infrastructure. In the road transport domain, schemes which are fully infrastructure-less and those which use a combination of fixed (infrastructure) devices and mobile devices fitted to vehicles and other moving objects are of significant interest to the ITS community as they have the potential to deliver a ‘connected environment’ where individuals, vehicles and infrastructure can co-exist and cooperate, thus delivering more knowledge about the transport environment, the state of the network and who indeed is travelling or wishes to travel. This may offer benefits in terms of real-time management, optimisation of transportation systems, intelligent design and the use of such systems for innovative road charging and possibly carbon trading schemes as well as through the CVHS (Cooperative Vehicle and Highway Systems) for safety and control applications. As the wireless sensor networks technology is still relatively new and very little is known about its real application in the transport domain. Our involvement in the transport-related projects provides us with an opportunity to carry out research and development of wireless sensor network applications in transport systems. This chapter outlines our experience in the ASTRA (ASTRA, 2005), TRACKSS (TRACKSS, 2007) and EMMA (EMMA, 2007) projects and provides an illustration of the important role that the wireless sensor technology can play in future ITS. This chapter also presents encouraging results obtained from the experiments in investigating the feasibility of utilising wireless sensor networks in vehicle and vehicle to infrastructure communication in real ITS applications

Indoor navigation for the visually impaired : enhancements through utilisation of the Internet of Things and deep learning

Wayfinding and navigation are essential aspects of independent living that heavily rely on the sense of vision. Walking in a complex building requires knowing exact location to find a suitable path to the desired destination, avoiding obstacles and monitoring orientation and movement along the route. People who do not have access to sight-dependent information, such as that provided by signage, maps and environmental cues, can encounter challenges in achieving these tasks independently. They can rely on assistance from others or maintain their independence by using assistive technologies and the resources provided by smart environments. Several solutions have adapted technological innovations to combat navigation in an indoor environment over the last few years. However, there remains a significant lack of a complete solution to aid the navigation requirements of visually impaired (VI) people. The use of a single technology cannot provide a solution to fulfil all the navigation difficulties faced. A hybrid solution using Internet of Things (IoT) devices and deep learning techniques to discern the patterns of an indoor environment may help VI people gain confidence to travel independently. This thesis aims to improve the independence and enhance the journey of VI people in an indoor setting with the proposed framework, using a smartphone. The thesis proposes a novel framework, Indoor-Nav, to provide a VI-friendly path to avoid obstacles and predict the user s position. The components include Ortho-PATH, Blue Dot for VI People (BVIP), and a deep learning-based indoor positioning model. The work establishes a novel collision-free pathfinding algorithm, Orth-PATH, to generate a VI-friendly path via sensing a grid-based indoor space. Further, to ensure correct movement, with the use of beacons and a smartphone, BVIP monitors the movements and relative position of the moving user. In dark areas without external devices, the research tests the feasibility of using sensory information from a smartphone with a pre-trained regression-based deep learning model to predict the user s absolute position. The work accomplishes a diverse range of simulations and experiments to confirm the performance and effectiveness of the proposed framework and its components. The results show that Indoor-Nav is the first type of pathfinding algorithm to provide a novel path to reflect the needs of VI people. The approach designs a path alongside walls, avoiding obstacles, and this research benchmarks the approach with other popular pathfinding algorithms. Further, this research develops a smartphone-based application to test the trajectories of a moving user in an indoor environment

New Approach of Indoor and Outdoor Localization Systems

Accurate determination of the mobile position constitutes the basis of many new applications. This book provides a detailed account of wireless systems for positioning, signal processing, radio localization techniques (Time Difference Of Arrival), performances evaluation, and localization applications. The first section is dedicated to Satellite systems for positioning like GPS, GNSS. The second section addresses the localization applications using the wireless sensor networks. Some techniques are introduced for localization systems, especially for indoor positioning, such as Ultra Wide Band (UWB), WIFI. The last section is dedicated to Coupled GPS and other sensors. Some results of simulations, implementation and tests are given to help readers grasp the presented techniques. This is an ideal book for students, PhD students, academics and engineers in the field of Communication, localization & Signal Processing, especially in indoor and outdoor localization domains

Integrated ZigBee RFID sensor networks for resource tracking and monitoring in logistics management

The Radio Frequency Identification (RFID), which includes passive and active systems and is the hottest Auto-ID technology nowadays, and the wireless sensor network (WSN), which is one of the focusing topics on monitoring and control, are two fast-growing technologies that have shown great potential in future logistics management applications. However, an information system for logistics applications is always expected to answer four questions: Who, What, When and Where (4Ws), and neither of the two technologies is able to provide complete information for all of them. WSN aims to provide environment monitoring and control regarded as When and What , while RFID focuses on automatic identification of various objects and provides Who (ID). Most people usually think RFID can provide Where at all the time. But what normal passive RFID does is to tell us where an object was the last time it went through a reader, and normal active RFID only tells whether an object is presenting on site. This could sometimes be insufficient for certain applications that require more accurate location awareness, for which a system with real-time localization (RTLS), which is an extended concept of RFID, will be necessary to answer Where constantly. As WSN and various RFID technologies provide information for different but complementary parts of the 4Ws, a hybrid system that gives a complete answer by combining all of them could be promising in future logistics management applications. Unfortunately, in the last decade those technologies have been emerging and developing independently, with little research been done in how they could be integrated. This thesis aims to develop a framework for the network level architecture design of such hybrid system for on-site resource management applications in logistics centres. The various architectures proposed in this thesis are designed to address different levels of requirements in the hierarchy of needs, from single integration to hybrid system with real-time localization. The contribution of this thesis consists of six parts. Firstly, two new concepts, Reader as a sensor and Tag as a sensor , which lead to RAS and TAS architectures respectively, for single integrations of RFID and WSN in various scenarios with existing systems; Secondly, a integrated ZigBee RFID Sensor Network Architecture for hybrid integration; Thirdly, a connectionless inventory tracking architecture (CITA) and its battery consumption model adding location awareness for inventory tracking in Hybrid ZigBee RFID Sensor Networks; Fourthly, a connectionless stochastic reference beacon architecture (COSBA) adding location awareness for high mobility target tracking in Hybrid ZigBee RFID Sensor Networks; Fifthly, improving connectionless stochastic beacon transmission performance with two proposed beacon transmission models, the Fully Stochastic Reference Beacon (FSRB) model and the Time Slot Based Stochastic Reference Beacon (TSSRB) model; Sixthly, case study of the proposed frameworks in Humanitarian Logistics Centres (HLCs). The research in this thesis is based on ZigBee/IEEE802.15.4, which is currently the most widely used WSN technology. The proposed architectures are demonstrated through hardware implementation and lab tests, as well as mathematic derivation and Matlab simulations for their corresponding performance models. All the tests and simulations of my designs have verified feasibility and features of our designs compared with the traditional systems