With the the emergence of the Internet-of-Things (IoT) and Cyber-Physical Systems (CPS), modern computing is now transforming from residing only in the cyber domain to the cyber-physical domain. I focus on one important aspect of this transformation, namely shortcomings of traditional security measures. Security research over the last couple of decades focused on protecting data in regard to identities or similar static attributes. However, in the physical world, data rely more on physical relationships, hence requires CPS to verify identities together with relative physical context to provide security guarantees. To enable such verification, it requires the devices to prove unique relative physical context only available to the intended devices. In this work, I study how varying levels of constraints on physical boundary of co-located devices determine the relative physical context. Specifically, I explore different application scenarios with varying levels of constraints – including smart-home, semi-autonomous vehicles, and in-vehicle environments – and analyze how different constraints affect binding identities to physical relationships, ultimately enabling IoT devices to perform such verification. Furthermore, I also demonstrate that sensing may pose risks for CPS by presenting an attack on personal privacy in a smart home environment.

This dissertation is directed towards improving the state of art cardiac monitoring methods and automatic diagnosis of cardiac anomalies through modern engineering approaches such as adaptive signal processing, and machine learning methods. The dissertation will describe the invention and associated methods of a cardiac rhythm monitor dubbed the Integrated Vectorcardiogram (iVCG). In addition, novel machine learning approaches are discussed to improve diagnoses and prediction accuracy of cardiac diseases. It is estimated that around 17 million people in the world die from cardiac related events each year. It has also been shown that many of such deaths can be averted with long-term continuous monitoring and actuation. Hence, there is a growing need for better cardiac monitoring solutions. Leveraging the improvements in computational power, communication bandwidth, energy efficiency and electronic chip size in recent years, the Integrated Vectorcardiogram (iVCG) was invented as an answer to this problem. The iVCG is a miniaturized, integrated version of the Vectorcardiogram that was invented in the 1930s. The Vectorcardiogram provides full diagnostic quality cardiac information equivalent to that of the gold standard, 12-lead ECG, which is restricted to in-office use due to its bulky, obtrusive form. With the iVCG, it is possible to provide continuous, long-term, full diagnostic quality information, while being portable and unobtrusive to the patient. Moreover, it is possible to leverage this ‘Big Data’ and create machine learning algorithms to deliver better patient outcomes in the form of patient specific machine diagnosis and timely alerts. First, we present a proof-of-concept investigation for a miniaturized vectorcardiogram, the iVCG system for ambulatory on-body applications that continuously monitors the electrical activity of the heart in three dimensions. We investigate the minimum distance between a pair of leads in the X, Y and Z axes such that the signals are distinguishable from the noise. The target dimensions for our prototype iVCG are 3x3x2 cm and based on our experimental results we show that it is possible to achieve these dimensions. Following this, we present a solution to the problem of transforming the three VCG component signals to the familiar 12-lead ECG for the convenience of cardiologists. The least squares (LS) method is employed on the VCG signals and the reference (training) 12-lead ECG to obtain a 12x3 transformation matrix to generate the real-time ECG signals from the VCG signals. The iVCG is portable and worn on the chest of the patient and although a physician or trained technician will initially install it in the appropriate position, it is prone to subsequent rotation and displacement errors introduced by the patient placement of the device. We characterize these errors and present a software solution to correct the effect of the errors on the iVCG signals. We also describe the design of machine learning methods to improve automatic diagnosis and prediction of various heart conditions. Methods very similar to the ones described in this dissertation can be used on the long term, full diagnostic quality ‘Big Data’ such that the iVCG will be able to provide further insights into the health of patients. The iVCG system is potentially breakthrough and disruptive technology allowing long term and continuous remote monitoring of patient’s electrical heart activity. The implications are profound and include 1) providing a less expensive device compared to the 12-lead ECG system (the “gold standard”); 2) providing continuous, remote tele-monitoring of patients; 3) the replacement of current Holter shortterm monitoring system; 4) Improved and economic ICU cardiac monitoring; 5) The ability for patients to be sent home earlier from a hospital since physicians will have continuous remote monitoring of the patients.

汽車行業已經發展了一百多年。由於價值鏈較長，供應鏈範圍廣泛，直接和間接就業人數眾多，所以在世界和許多國家的經濟中經常發揮關鍵作用。同時，由於技術含量高，進入壁壘高和供應鏈深度整合，汽車產業保持了穩定的結構。 近年來，互聯網（IoT）在社會上引起了更多的關注。硬件，軟件，商業模式和服務等方面的創新正在改變我們每一天的生活。一些行業和客戶的要求受到互聯網的影響。一些行業受到嚴重衝擊，例如阿里巴巴（Alipay）之於互聯網進入或Airbnb之於酒店業務。 客戶滿意度的競爭是公司發展和戰略的關鍵要素之一。客戶需求直接影響客戶滿意度;快速變化的客戶期望迫使公司做出迅速反應。創新是創意的應用;這可能是滿足新出現的客戶期望的方式之一，並提高客戶滿意度。 本研究將重點關注汽車產業;豪華品牌汽車公司因其創新的品牌認知和策略而被選中。本研究是基於與供應商，汽車製造商，經銷商和客戶等價值鏈夥伴的訪談。通過半結構化訪談和次級文件收集的方法，調查了互聯網技術如何影響產品和售後服務的創新以及汽車行業的客戶滿意度。 從分析收集和回顧行業實踐的數據得出的結論可以作為汽車行業參考，用於製定創新戰略和經營策略，以適應加速變化的商業環境。 / The automotive industry has been developing for more than 100 years. Because of the long value chain, the wide range of supply chain and the high amount of direct and indirect employments involved, it always plays a key role in the economy of the world and many countries. Meanwhile, because of the high technology, the finance entry barrier and the deeply integrated supply chain, the structure of automotive industry remains stable and consolidated, so far. In the recent years, the Internet of Things (IoT) has attracted more attention in the society. The innovations on hardware, software, business models and services etc. are changing our life every day. Some industries and customer requirements have been impacted by the IoT, either visibly or unconsciously. Some industries have been heavily disrupted, e.g. the internet finance by Alibaba (Alipay) or the hotel business by Airbnb. The competition in Customer Satisfaction is one of the key elements of a company development and strategy. The customer requirement affects customer satisfaction directly; the fast changing customer’s expectations are forcing the companies to react dynamically. Innovation is the application of new ideas; this could be one of the ways to meet newly appeared customer’s expectations, and improve customer satisfaction. This study will focus on automotive industry; a luxury brand automotive company is selected due to its innovative brand equity and strategy. The study is based on interviews with the partners in value chain such as suppliers, automotive manufacturers, dealers and customers. With the help of semi-structured interviews and secondary documents collection, this study investigates how the IoT technology impacts the innovation on product and Aftersales, as well as the customer satisfaction in automotive industry. The conclusions drawn from analyzing the data collected and reviewing the industry practices can be used as a reference by the automotive industry for making innovation strategy and business strategy in order to adapt to the accelerated moving environment.

In order to implement wireless sensing and monitoring services at large scale, Internet connection is highly desirable. Particularly, TCP is indispensable for end-to-end connection orientated communication. It is well known that low power and low rate IEEE802.15.4 based Wireless Sensor Networks (WSNs) are vulnerable to the interference from collocated Wireless Local Area Networks (WLAN) utilizing the same un-licensed 2.4GHz frequency band. Such coexistence interference seriously deteriorates the performance of TCP/IPv6 over WSN, resulting in packet losses, disconnections, reduced throughput and so on. This thesis focuses on experimental research on the performance evaluation and improvement of TCP/IPv6 over IEEE 802.15.4 based WSN. In this research, a versatile testbed has been developed and implemented, which consists of off-the-selves and custom built hardware, open source and in-house developed firmware and software. A periodical monitoring/sensing application that uses TCP to transmit data over WSN has been developed and used for performance evaluation when there is various Wi-Fi interference close by. Based on the observations and analysis of our experimental results, several important parameters that impact the TCP packet transmission performance have been identified. Performance improvement technique is proposed to effectively adjust these parameters so as to support periodic monitoring/sensing application with substantial better performance. Extensive experiments have been performed in the testbed to evaluate the performance of WSN packets transmission via TCP over WSN when subjected to different Wi-Fi interference.

La utilidad del entorno IoT en la innovación, la reducción de costos, y el levantamiento de información para beneficio de organizaciones públicas y privadas.

The advances in the technology and the emergence of low complexity intelligent devices result in the evolution of the Internet-of-Things (IoT). In most IoT application scenarios, billions of things are interconnected together using standard communication protocols to provide services for different applications in the healthcare industry, smart cities, transportation, and food supply chain. Despite their advantage of connecting things anywhere, anytime, and anyplace, IoT presents many challenges due to the heterogeneity, density, the power constraints of things, and the dynamic nature of the network that things might connect and disconnect at any time. All of these increase the communication delay and the generated data, and it is thereby necessary to develop resource management solutions for the applications in IoT. One of the most important resources is the wireless channel, which is a shared resource; thus, it is necessary for the nodes to have methods that schedule channel access. This thesis considers the problem of distributed sensing and channel access in the context of IoT systems, where a set of selfish nodes competes for transmission opportunities. In the channel access part, a memory-one channel access game is proposed to reduce the collision rate, to enhance the cooperation among the nodes, and to maximize their payoffs by optimizing their channel access probabilities, based on the channel state in the previous time step. To overcome the communication cost overhead in the network and to solve the problem efficiently, the nodes use distributed learning algorithms. Next, the problem is extended to include energy constraints on the transmission decisions of the nodes, where each one of them has a battery of finite capacity, which is replenished by an energy-harvesting process. This constrained problem is solved using energy-aware channel access games under different scenarios of perfect and imperfect information. In the distributed sensing part, a traffic-monitoring system, integrated into a WSN, is proposed as a potential application to implement the channel access solution. This system maximizes the privacy of the sensed traffic by using low-cost and low-power sensor devices that integrate passive infrared sensors (PIR) and ultrasonic range finders. To estimate the parameters required to solve the real-time monitoring problem (vehicle detection, classification, and speed estimation), the measurements of these sensors are analyzed using a set of optimized machine-learning algorithms. The selection of these algorithms is due to the continuous variation of the sensed environment over time, the lack of the system state dynamic models, and the limitation in the resources.

Time and again we have seen the Internet grow and evolve at an unprecedented scale. The number of online users in 1995 was 40 million but in 2020, number of online devices are predicted to reach 50 billion, which would be 7 times the human population on earth. Up until now, the revolution was in the digital world. But now, the revolution is happening in the physical world that we live in; IoT devices are employed in all sorts of environments like domestic houses, hospitals, industrial spaces, nuclear plants etc., Since they are employed in a lot of mission-critical or even life-critical environments, their security and reliability are of paramount importance because compromising them can lead to grave consequences. IoT devices are, by nature, different from conventional Internet connected devices like laptops, smart phones etc., They have small memory, limited storage, low processing power etc., They also operate with little to no human intervention. Hence it becomes very important to understand IoT devices better. How do they behave in a network? How different are they from traditional Internet connected devices? Can they be identified from their network traffic? Is it possible for anyone to identify them just by looking at the network data that leaks outside the network, without even joining the network? That is the aim of this thesis. To the best of our knowledge, no study has collected data from outside the network, without joining the network, with the intention of finding out if IoT devices can be identified from this data. We also identify parameters that classify IoT and non-IoT devices. Then we do manual grouping of similar devices and then do the grouping automatically, using clustering algorithms. This will help in grouping devices of similar nature and create a profile for each kind of device.

No description available.

Sowohl das Architekturmuster der Microservices als auch das „Internet of Things“ (IoT) folgen den Prinzipien verteilter Systeme. Eine Anwendung von Microservices im IoT ist daher naheliegend, allerdings stellt sich hierbei die Frage,welche Integrationsform dafürambesten geeignet ist. Aus diesem Grund besteht das Ziel dieser Arbeit darin, verschiedene Kommunikationskonzepte von Microservices auf ihre Eignung für den Bereich des IoTs zu überprüfen. In der Arbeit werden dafür verschiedene Kommunikationskonzepte vorgestellt und anhand von diversen Kriterien miteinander auf qualitative Weise verglichen. Die Kriterien setzen sich aus allgemeinen Herausforderungen im Umgang mit verteilten Systemen sowie aus kennzeichnenden Eigenschaften für IoT-Systeme, wie bspw. Skalierbarkeit, Erweiterbarkeit und Ressourcennutzung zusammen. Ergänzend dazu fließen weitere Aspekte der Softwareentwicklung in den Vergleich ein. Anhand der Vergleichsergebnisse wird schließlich eine Bewertung durchgeführt, welche als Grundlage für die Entwicklung von Microservices im Bereich IoT dienen kann. Zum Ende wird das Resultat durch die Konzeption einer eigenen Anwendung erprobt. Der Vergleich und die anschließende Bewertung zeigen, dass sich asynchrone Microservices aufgrund ihrer Eigenschaften am besten für den Einsatz im IoT eignen. Dabei wurde insbesondere auf die die Kommunikationsvariante des Messagings mittels des Protokolls MQTT eingegangen. Aufbauend auf den Ergebnissen dieser Arbeit könnten Forschungen im Bereich moderner IoT-Plattformen angestellt werden. Weiterhin würde sich die Erweiterung bestehender Microservice-Anwendungen durch zusätzliche Services für Datensammlung und intelligente Auswertung dieser als Forschungsthema anbieten.:1 Einleitung und Intention 1.1 MakroSolutions GmbH 1.2 Stand der Wissenschaft und Technik 1.3 Ziel der Arbeit 1.4 Aufbau der Arbeit 2 Definitionen und theoretische Grundlagen 2.1 Verteilte Systeme 2.1.1 Services 2.2 Internet of Things 2.2.1 Industrial Internet of Things 2.3 Microservices 2.3.1 Definition und Eigenschaften 2.3.2 Vorteile im Umgang mit Microservices 2.3.3 Herausforderungen im Umgang mit Microservices 2.3.4 Anwendungsgebiete 2.3.5 Abgrenzung zu monolithischer Architektur 2.3.6 Abgrenzung zu Service-Orientierter Architektur (SOA) 3 Kommunikation der Microservices 3.1 Mikro- und Makroarchitektur 3.2 Integrationsformen 3.3 Gemeinsame Datenbanknutzung und Datenreplikation 3.4 Synchrone Microservices 3.5 Asynchrone Microservices 4 Vergleich und Bewertung 4.1 Wahl der Vergleichskriterien 4.1.1 Fallacies of distributed computing 4.1.2 CAP-Theorem 4.1.3 Internet of Things 4.1.4 Weitere qualitative Kriterien 4.2 Vergleich der Kommunikationskonzepte 4.2.1 Fehlertoleranz und Resilienz 4.2.2 Performance und Ressourcennutzung 4.2.3 Datenkonsistenz und Verfügbarkeit 4.2.4 Skalierbarkeit und Erweiterbarkeit 4.2.5 Kopplung 4.2.6 Komplexität 4.2.7 Tests 4.2.8 Sicherheit 4.3 Bewertung in Bezug auf das Internet der Dinge (IoT) 5 Konzeption der Software 5.1 Ausgangspunkt 5.2 Anforderungen 5.3 Vorüberlegungen 5.4 Konzeption 6 Auswertung und Ausblick 6.1 Zusammenfassung und Interpretation der Ergebnisse 6.2 Beschränkungen und Ausblick für weitere Forschung

This work deal with analysis of LoRa wireless communication protocol and LoRaWAN MAC layer. Analysis aims to LoRa packet detection using software defined radio, wireless trafic and information which can be extracted (sniffed) from wireless communication between devices which uses LoRaWAN MAC layer. Next part of this work describes two wireless devices development. First one for demonstration purporses with some type of commercial LoRa modules and second to paralell sniffing of LoRa wireless communication on various frequency channels.