The application of Wireless Sensor Networks (WSNs) with a large number of tiny, cost-efficient, battery-powered sensor nodes that are able to communicate directly with each other poses many challenges. Due to the large number of communicating objects and despite a used CSMA/CA MAC protocol, there may be many signal collisions. In addition, WSNs frequently operate under harsh conditions and nodes are often prone to failure, for example, due to a depleted battery or unreliable components. Thus, nodes or even large parts of the network can fail. These aspects lead to reliable data dissemination and data storage being a key issue. Therefore, these issues are addressed herein while keeping latency low, throughput high, and energy consumption reduced. Furthermore, simplicity as well as robustness to changes in conditions are essential here. In order to achieve these aims, a certain amount of redundancy has to be included. This can be realized, for example, by using network coding. Existing approaches, however, often only perform well under certain conditions or for a specific scenario, have to perform a time-consuming initialization, require complex calculations, or do not provide the possibility of early decoding. Therefore, we developed a network coding procedure called Broadcast Growth Codes (BCGC) for reliable data dissemination, which performs well under a broad range of diverse conditions. These can be a high probability of signal collisions, any degree of nodes' mobility, a large number of nodes, or occurring node failures, for example. BCGC do not require complex initialization and only use simple XOR operations for encoding and decoding. Furthermore, decoding can be started as soon as a first packet/codeword has been received. Evaluations by using an in-house implemented network simulator as well as a real-world testbed showed that BCGC enhance reliability and enable to retrieve data dependably despite an unreliable network. In terms of latency, throughput, and energy consumption, depending on the conditions and the procedure being compared, BCGC can achieve the same performance or even outperform existing procedures significantly while being robust to changes in conditions and allowing low complexity of the nodes as well as early decoding. / Der Einsatz von drahtlosen Sensornetzen (Wireless Sensor Networks, WSNs) mit einer Vielzahl hochintegrierter, kostengünstiger und batteriebetriebener Sensorknoten, die direkt miteinander kommunizieren können, birgt viele Herausforderungen. Aufgrund der großen Anzahl von kommunizierenden Objekten kann es trotz eines verwendeten CSMA/CA MAC Protokolls zu vielen Signalkollisionen kommen. Darüber hinaus arbeiten WSNs häufig unter rauen Bedingungen und die Knoten sind oft anfällig für Ausfälle, z.B. aufgrund aufgebrauchter Energiekapazität oder defekter Komponenten. Infolgedessen können einzelne Knoten oder auch große Teile des Netzes ausfallen. Diese Aspekte führen dazu, dass zuverlässige Datenverteilung und Datenhaltung von entscheidender Bedeutung sind und folglich im Rahmen dieser Arbeit adressiert werden. Gleichzeitig soll die Latenz niedrig, der Durchsatz hoch und der Energieverbrauch möglichst gering gehalten werden. Des Weiteren sind eine geringe Komplexität sowie Robustheit gegenüber veränderten Bedingungen wesentlich. Um diese Ziele zu erreichen, ist ein gewisses Maß an Redundanz nötig. Dies kann beispielsweise durch die Verwendung von Netzwerkkodierung realisiert werden. Bestehende Ansätze liefern jedoch oft nur unter bestimmten Bedingungen oder für ein spezifisches Szenario gute Performanz-Ergebnisse, müssen aufwändig initialisiert werden, benötigen komplexe Berechnungen oder bieten keine Möglichkeit für frühzeitige Dekodierung. Daher haben wir ein als Broadcast Growth Codes (BCGC) bezeichnetes Netzwerkkodierungsverfahren für zuverlässige Datenverteilung entwickelt, welches unter einem breiten Spektrum unterschiedlicher Bedingungen gute Ergebnisse erzielt. Zu diesen Bedingungen gehören zum Beispiel eine hohe Wahrscheinlichkeit von Signalkollisionen, ein beliebiger Grad an Knotenmobilität, eine große Knotenanzahl oder das Auftreten von Knotenausfällen. BCGC benötigen keine komplexe Initialisierung und verwenden nur einfache XOR-Operationen für Kodierung und Dekodierung. Darüber hinaus kann mit der Dekodierung bereits begonnen werden, sobald ein erstes Paket/Codewort empfangen wurde. Evaluationen mit einem eigens implementierten Netzwerksimulator sowie einem realen Testbed haben gezeigt, dass BCGC ermöglichen, Daten trotz eines unzuverlässigen Netzwerks zuverlässig zu erhalten. In Bezug auf Latenz, Durchsatz und Energieverbrauch können BCGC, je nach Bedingungen und verglichenem Verfahren, vergleichbare Ergebnisse wie bestehende Verfahren erzielen oder diese sogar deutlich übertreffen, während sie gleichzeitig robust gegenüber veränderten Bedingungen sind, eine geringe Komplexität der Knoten erlauben sowie eine frühzeitige Dekodierung ermöglichen.

The Internet of Things is expanding, and with the increasing numbers of connected devices,exploitation of those devices also becomes more common. Since IoT devices and IoT networksare used in many crucial areas in modern societies, ranging from everything between securityand militrary applications to healthcare monitoring and production efficiency, the need to securethese devices is of great importance for researchers and businesses. This project explores howan intrusion detection system called DETONAR can be used on border router logs, instead of itsoriginal use of sniffer devices. Using DETONAR in this way allows us to detect many differentattacks, without contributing to the additional cost of deploying sniffer devices and the additionalrisk of the sniffer devices themselves becoming the target of attack

Internet of things (IoT) möjliggör innovation i hemmet med extra bekvämligheter och värde inom en mängd olika domäner. Allt oftare utrustas städer, hushåll och kontorsmiljöer med smarta säkerhetslösningar som syftar till att öka individers säkerhet. Samtidigt återfinns det svaga säkerhetsimplementeringar i allt flera system. Det finns en mängd etablerade risker med att använda ett smart hem och när man då väljer att kombinera det med ett säkerhetssystem blir konsekvenserna av ett eventuellt dataintrång omfattande för den personliga integriteten.     Syftet med denna studie är att bidra med kunskap kring vilka betydande säkerhetsrisker som identifieras vid användandet av säkerhetssystem i hemmet, samt hur medvetna användare är gällande riskerna när de implementerar säkerhetssystem i det smarta hemmet. De frågeställningar som ligger till grund för studien är: ”Utifrån aktuell forskning, vilka betydande säkerhetsrisker kan identifieras vid användning av säkerhetssystem i det smarta hemmet?”, ”Är användarna medvetna om riskerna med säkerhetssystem i det smarta hemmet? ” och ”Vilka säkerhetslösningar implementerar ovannämnda användare?”. För att besvara frågeställningarna har en blandad metodologi använts genom en litteraturundersökning och en enkätundersökning, där presenterades riskerna och respondenterna fick besvara hur medvetna de var om dessa risker.   Resultatet visar att respondenterna har hög medvetenhet om riskerna med säkerhetssystem i det smarta hemmet. Av studien framgår det att respondenterna i stor utsträckning kan beskriva de eventuella risker som ett säkerhetssystem i det smarta hemmet medför. Enkätundersökningen visar även att till stor del har de flesta teknisk utbildning och att majoriteten av respondenterna var män. Notera att utbildning, kön och ålder är ett intressant öppet problem att utföra undersökningen på när det gäller mer inhomogena grupper, dock ligger det utanför den valda problemställningen. Det kan vara av intresse i framtida forskning att utföra studien på inhomogena grupper för att få mer nyanserade svar.

The purpose of this thesis rose from tackling a specific project led by Cybercom Group. Water Sense was proposed after municipalities expressed the need to conveniently conduct measurements on water in Swedish lakes, and remotely get access to these data. The varying and infrequent nature of measurements result in an inefficient power consumption when a conventional sensor platform is used. Internet of Things is a relatively new and ever-evolving field for wireless sensor networks, where Low Power Wide-Area Network protocols are utilized to cleverly save power. One of these LPWAN protocols is LoRaWAN, a MAC layer protocol that runs on top of the PHY layer protocol LoRa. The chosen platform hardware for sensor nodes is an Adafruit feather equipped with a LoRa radio module, and the Contiki operative system was to be imported and integrated. Contiki OS is developed for small IoT systems with low-power, while offering networking mechanisms and a range of protocols typically utilized in WSNs. The adaptive and modular nature of Contiki allows for custom pairing of protocols to target a specific topology. LoRaWAN has a number of constraints that are disadvantageous for Water Sense, most prominently being a single-hop protocol. Contiki already supports several platforms with drivers, but the CPU and radio module of the Adafruit feather are not one of them. The goal was to integrate the LoRa PHY hardware with Contiki and have an adaptive platform for Water Sense and other scenarios. Unfortunately not all initial goals were achieved, and the physical layer was not fully integrated with Contiki’s APIs. However, the drivers needed for an operational physical layer were completed and range test could be conducted. Therefore, this thesis details the work done for implementing the physical layer and a study on Contiki’s data link protocols in proposed configurations for Water Sense.

Framväxten av antalet smarta enheter som är integrerade med Internet har lett till att behovet av Internet-of-Things ökar i olika tillämpningar, nämligen inom industrier fabrikstillverkning. Projektets huvudsakliga syfte är att implementera ett styrsystem med hjälp av Industrial Ethernet och användningen av Profinet protokoll som användargränssnitt. Denna studies huvudsakliga uppgift är undersöka prestandan av detta system och vilken skalbarhet man kan få ut ur den, dessutom utföra olika typer av tester för att mäta responstiden hos detta system med hjälp av real-time system. Studien lyfter upp IIoT funktionalitet, dess featureprogram och möjligheten att den implementeras på bred tillgänglig hårdvara. Det slutliga resultatet av tidmätningarna kunde i genomsnitt visa hur lång tid det tar för en signal att skickas inom ett Profinet-Nätverk. Mer speciellt, så tar en signal i genomsnitt 0,97ms. , vilket är relevant kort tid i förhållande till projektanpassningar inom industrier. Den beräknade standardavvikelsen visar på de erhållna värdenas noggrannhet, då den visade hur utspridda värdena är och hur mycket håller de sig till de beräknade medelvärdena. Utförande av Stresstesten bidrog till att dra slutsatser om systemets prestanda. Då de olika medelvärdena visade hur antalet signaler skiljer sig i förhållande till Cykel-tidsändringen. Resultatet av denna test visade också maximala antalet paket/signaler som kan skickas inom en begränsad tid. Dessutom presenterade resultatet gränsvärdet av det minimala antalet signaler som kan skickas oavsett hur mycket Cykel-tiden ökas eller minskas. Mer specifikt, visade detta system att det kan skicka 3250 signal inom en begränsad tid (60 s) vid Cykel-tid (1), och det kan skicka minst 1500 signaler inom samma begränsade tid. Det slutliga resultatet förslog ett par framtida arbete, det första var att utföra ett Profinet-system med hjälp av trådlösa fältbussar, och jämföra det med denna studies resultat för mer pålitlig implementation. Den andra var utreda säkerhet och krypteringen av Industrial Ethernet, detta skulle ge oss en bild om hur säkert att adoptera denna teknik. / The growth of the number of smart devices that are integrated into the Internet has led to an increase in the need for Internet-of-Things in various applications, namely in industries and manufacturing plants. The main purpose of the project is to implement a control system using Industrial Ethernet with the use of Profinet protocol as a user interface. This study will mainly examine the performance of this system and what scalability can be obtained from it, in addition to, performing various types of tests to measure the response time of this system by using real-time systems. The study highlights IIoT functionality, its feature program and the possibility that it is implemented on readily available hardware. The final results of time measurements could show on average how long a signal takes to be sent within a Profinet Network. More specifically, a signal takes an average of 0.97ms. The calculated standard deviation indicates the accuracy of the values obtained, as it showed that they scattered to the calculated mean values. Performing the Stress Test helped to draw conclusions about the performance of the system. These calculated different averages showed how the number of signals differs in relation to the Cycle time change. The result of this test also showed the maximum number of packets / signals that can be sent within a limited time. In addition, the result presented the limit values of the minimum number of signals that can be sent regardless of how much the “Cycle Clock” is increased or decreased. More specifically, this system showed that it can send 3250 signals within a limited time 60 (s) at Cycle time 1, and it can send at least 1500 signals within the same limited time. The final result suggested a couple of future work, the first was to perform a Profinet system by using wireless fieldbuses and compare it with the results of this study for more reliable implementation. The second was to investigate the security and encryption of Industrial Ethernet, this would give us an idea of how secure to adopt this technology.

Wireless sensor networks used in smart cities and elsewhere collect large amounts of sensor data that needs to be made available to respective audiences and have proper visualization. There is a lack of mobile applications capable of visualizing sensor data coming from multiple sources using different protocols and data formats in a clear way; an application that is easy for anyone to use. This paper will present the development and evaluation of Smart City IoT which is an Android application for visualization of IoT data collected from wireless sensor networks. The resulting application Smart City IoT is designed to be modular to the core to allow for easy extension with new sensor types, communication protocols and data formats. It demonstrates that an Android application can be developed to support multiple sources with different protocols and have a unified visualization without requiring extensive set up. / Trådlösa sensornät som används i smarta städer och på annat håll samlar in stora mängder data som behöver göras tillgängliga för respektive publik och använda sig av lämpliga visualiseringar. Det är brist på mobila applikationer som är kapabla att visualisera sensordata som kommer från flera källor med olika protokoll och data format på ett tydligt sätt; en applikation som är enkel att använda. Den här rapporten kommer att presentera utvecklingen och valideringen av Smart City IoT vilket är en applikation till Android för att visualisera IoTdata hämtat från trådlösa sensor-nätverk. Den resulterande applikationen Smart City IoT är designad för att vara modulär i sin kärna för att tillåta enkel utbyggnad av nya sensortyper, kommunikationsprotokoll och dataformat. Den demonstrerar att en applikation för Android kan utvecklas med stöd för flera källor, med olika protokoll och ha en gemensam visualisering utan att kräva en omfattande konfiguration.

This report investigates reliability within the Internet of Things with a focus on the messaging protocol MQTT. Within MQTT we explore the options for ensuring reliability, mainly Quality of Service. We attempt to compare a few different implementations of the MQTT protocol over different Quality of Service levels. This comparison occurs through experiments that measure the communication size in bytes, and the time to perform, a simple publish-type communication. We find that there are some differences that seem likely to be impactful enough that some implementations are preferable, depending on the application and resources available. This report also covers some basic theory about IoT systems and their parts.

This thesis focuses on the design and implementation of a new, inexpensive, and less complex system for a Do-It-Yourself (DIY) Internet of Things (IoT) platform. The hardware aspects focus on a new chip called the ESP8266 which contains both microcontroller and WiFi connectivity capabilities in an extremely affordable package. The system uses the Arduino IDE to program the ESP8266, which is known to be an extremely user-friendly environment. All other software is both free and easy to use. Past methods of creating IoT projects involved either expensive hardware, often ranging from $50-$100 per node, or complicated programming requiring a full computer, or a constant connection to an immobile power source. This method costs as little as $2.50, can last for months or even years off of batteries, can be smaller than a quarter, and only requires a few lines of code to get data moving, making this platform much more attractive for ubiquitous use.

Internet of Things (IoT) devices have been widely adopted in many different applications in recent years, such as smart home applications. An adversary can capture the network traffic of IoT devices and analyze it to reveal user activities even if the traffic is encrypted. Therefore, traffic privacy is a major concern, especially in smart home applications. Traffic shaping can be used to obfuscate the traffic so that no meaningful predictions can be drawn through traffic analysis. Current traffic shaping methods have many tunable variables that are difficult to optimize to balance bandwidth overheads and latencies. In this thesis, we study current traffic shaping algorithms in terms of computational requirements, bandwidth overhead, latency, and privacy protection based on captured traffic data from a mimic smart home network. A new traffic shaping method - Dynamic Traffic Padding is proposed to balance bandwidth overheads and delays according to the type of devices and desired privacy. We use previous device traffic to adjust the padding rate to reduce the bandwidth overhead. Based on the mimic smart home application data, we verify our proposed method can preserve privacy while minimizing bandwidth overheads and latencies.

Smart agriculture is an increasingly popular field in which the technology of wireless sensor networks (WSN) has played a large role. Significant research has been done at Cal Poly and elsewhere to develop a computer vision (CV) and machine learning (ML) pipeline to monitor crops and accurately predict crop yield numbers. By autonomously providing farmers with this data, both time and money are saved. During the past development of a prediction pipeline, the primary focuses were CV and ML processing while a lack of attention was given to the collection of quality image data. This lack of focus in previous research presented itself as incomplete and inefficient processing models. This thesis work attempts to solve this image acquisition problem through the initial development and design of an Internet of Things (IoT) prototype network to collect consistent image data with no human interaction. The system is developed with the goals of being low-power, low-cost, autonomous, and scalable. The proposed IoT network nodes are based on the ESP32 SoC and communicate over-the-air with the gateway node via Bluetooth Low Energy (BLE). In addition to BLE, the gateway node periodically uplinks image data via Wi-Fi to a cloud server to ensure the accessibility of collected data. This research develops all functionality of the network, comprehensively characterizes the power consumption of IoT nodes, and provides battery life estimates for sensor nodes. The sensor node developed consumes a peak current of 150mA in its active state and sleeps at 162µA in its standby state. Node-to-node BLE data transmission throughput of 220kbps and node-tocloud Wi-Fi data transmission throughput of 709.5kbps is achieved. Sensor node device lifetime is estimated to be 682 days on a 6600mAh LiPo battery while acquiring five images per day. This network can be utilized by any application that requires a wireless sensor network (WSN), high data rates, low power consumption, short range communication, and large amounts of data to be transmitted at low frequency intervals.