The Internet of Things (IoT) consists of a network of physical devices that are connected over the internet for the purpose of exchanging data with other devices and systems. IoT platforms, such as Node-RED, have been introduced in recent times to facilitate communication between different IoT devices. Hosting Node-RED on a cloud service provider might result in the confidentiality of sensitive data on Node-RED being violated by malicious attackers, since users are forced to entrust their sensitive data with the cloud service providers. Using trusted execution environments, such as AMD-SEV and Intel SGX, can mitigate several potential attacks from exposing sensitive information in Node-RED. This thesis investigates if AMD-SEV and Intel SGX are viable options to protect sensitive data in Node-RED when hosted on a cloud service provider. The work in this thesis investigates difficulties encountered when deploying Node-RED on AMD-SEV and Intel SGX, from a usability perspective. Usability is measured by running Node-RED in AMDSEV and Intel SGX, and then recording the complexity of the process. Several performance tests are conducted to measure the performance overhead of Node-RED caused by AMD-SEV. A literature review is also conducted to investigate potential vulnerabilities in AMD-SEV and Intel SGX that could undermine the security of user’s data in Node-RED. The results from this thesis finds that AMD-SEV is a viable option to protect sensitive data in Node-RED when hosted on a cloud service provider. Deploying Node-RED on AMD-SEV is found to be a relatively simple process from a usability perspective. There are some noticeable performance overhead with regards to CPU utilization and TCP throughput, but all other metrics show marginal performance overhead. The potential vulnerabilities in AMD-SEV are not found to be significant enough to make AMD-SEV unviable. The thesis finds Intel SGX to be an unviable solution primarily due to usability. The process of running Node-RED in an Intel SGX enclave is extremely complex and the results show that for most users of Node-RED, this is not viable. The security vulnerabilities found from the literature review, are not significant enough to make Intel SGX an unviable option to protect sensitive user data inNode-RED. / Internet of Things (IoT) är en nätverk av fysiska enheter som är sammankopplade via internet för att kunna skicka data till andra fysiska enheter eller system. IoTplattformar, som Node-RED, har utvecklats för att förenkla kommunikationen mellan olika IoT- enheter. Att köra Node-RED på en molntjänst kan leda till att sekretessen av känslig data på Node-RED blir kränkt av en attack mot molntjänsten. Det är på grund av att användarna av Node-RED är tvungna att tillförlita deras känsliga data till molntjänsten, som deras data kan bli kränkt. Detta problem kan förminskas genom att användarna utnyttjar trusted execution environments som AMD-SEV och Intel SGX för att skydda sin känsliga data på molntjänsten. I denna avhandling, undersöks det om AMDSEV och Intel SGX kan användas för att skydda data i Node-RED när den körs på en molntjänst. Användarvänligheten av att köra Node-RED med AMD-SEV och Intel SGX undersöks genom att uppskatta hur komplicerad denna process är. Flera tester genomförs också för att mäta vilken påverkan AMD-SEV har på prestandan av Node-RED. En litteraturöversikt genomförs också för att undersöka potentiella sårbarheter i AMD-SEV och Intel SGX som skulle kunna utnyttjas för att komma åt känslig data i Node-RED. Resultaten från avhandlingen visar att AMD-SEV kan vara användbart för att skydda känslig data i Node-RED när den körs på en molntjänst. AMDSEV är väldigt användarvänlig när Node-RED ska köras. AMD-SEV har en märkbar påverkan på prestandan av processorn och TCP- genomströmning, men för de andra faktorerna som mäts har AMD-SEV ingen större påverkan. Litteraturöversikten finner inga sårbarheter som är tillräckligt farliga för att göra AMD-SEV oanvändbar för att skydda känslig data iNode-RED. Resultaten från avhandlingen visar dock att Intel SGX inte är särskilt användbar för att skydda känslig data i Node-RED när den körs på en molntjänst. Detta är främst för att det är väldigt komplicerat att köra Node-RED i en Intel SGX enklav från en användarvänlighet synpunkt. De flesta av Node-REDs användare skulle finna det för komplicerat att använda Intel SGX för att skydda sin känsliga data. Litteraturöversikten finner inga sårbarheter allvarliga nog för att göra Intel SGX oanvändbar.

Forklift vehicles used for moving pallets and boxes in warehouses, have recently been integrated with Internet of Things (IoT) technology, in effect making forklifts networked and in parts controllable from afar. Human operators now carry out tasks according to instructions displayed on the screen of the IoT-forklift instead of just maneuvering around and executing tasks as they see fit. Through an autobiographical design process, hazardous situations arising because of limitations at the interface of the IoT-forklifts were revealed. To address these hazardous situations, we propose changing the interface of the forklift to better monitor the pick-up and dropping of packages. Changes to the digitally-enabled interface was done through the implementation of modalities. In short three modalities was considered, tactile, visual and auditive ones. While the tactile modality was not deemed to be feasible, the visual and auditive modalities was prototyped and evaluated through an Wizard of Oz method. Colored LED light strips showed to improve the handling, locating, selecting and moving the correct goods within the warehouse while keeping both operators and items safe. Further improvements to the digitally-enabled infrastructure in the warehouse that can optimize the routes to and from the pickup were devised. Cameras, sensors and lasers installed on advantageous places within the warehouse and on the forklift will help keeping track on both the forklift operators and the items during pick - and drop operations. As a result the system will have an awareness of its environment were both efficiency and safety will be further improved. / Gaffeltruckar som används for att flytta pallar och lådor i lager har nyligen integrerats med IoT-teknologin (Internet of Things), vilket gör gaffeltruckar i nätverk och i delar kontrollerbara långt ifrån. Mänskliga operatörer utför nu uppgifter enligt instruktionerna som visas på IoT-gaffeltruckens skärm istället för att bara manövrera runt och utföra uppgifter som de anser lämpligt. Genom en självbiografisk designprocess avslöjades farliga situationer som uppstod på grund av begränsningar vid gränssnittet mellan IoT-gaffeltruckarna. För att hantera dessa farliga situationer föreslår vi att man ändrar gaffeltruckens gränssnitt för att bättre övervaka hämtning och släppande av paket. Ändringar av det digitalt aktiverade gränssnittet gjordes genom implementering av modaliteter. Kort sagt övervägdes tre metoder, taktila, visuella och auditiva. Även om den taktila modaliteten inte ansågs vara genomförbar prototyperades och utvärderades de visuella och auditiva metoderna genom en Wizard of Oz-metod. Färgade LED-ljusremsor visade sig förbättra hanteringen, lokaliseringen, valet och flyttandet av de rätta varorna inom lagret och samtidigt hålla både operatörer och föremål säkra. Ytterligare förbättringar av den digitalt aktiverade infrastrukturen i lagret som kan optimera rutterna till och från upphämtningen planerades. Kameror, sensorer och lasrar installerade på fördelaktiga platser i lagret och på gaffeltrucken hjälper till att hålla koll på både gaffeltruckoperatörema och föremålen under plock - och släppoperationer. Som ett resultat kommer systemet att känna till sin miljö där både effektivitet och säkerhet kommer att förbättras ytterligare.

The rapid proliferation of the Internet of Things (IoT) devices and the growing demand for intelligent systems have driven the development of low-power, compact, and efficient machine learning solutions. Deep neural networks (DNNs) have become state-of-the-art algorithms in various applications, such as face recognition, object detection, and speech recognition, due to their exceptional accuracy. In terms of edge devices, it is ideal to execute these algorithms locally on devices rather than on servers to mitigate data transfer latency and address privacy concerns. Reducing power consumption and enhancing energy efficiency becomes crucial, as mobile and wearable devices typically have limited battery capacity. Low-power consumption can extend battery life, reduce recharging cycles, and thus decrease maintenance costs. Ultra-Low-power AI hardware has increasingly garnered attention due to its potential to enable numerous compelling applications. This technology can serve as an always-on wake-up module, such as keyword spotting and visual wake-up, to facilitate hierarchical data processing. Addi-tionally, it can be employed in security and surveillance applications on battery-powered cameras and miniaturized drones. Various techniques to reduce power consumption have been proposed at individual levels, encompassing algorithms, architecture, and circuits. Application-oriented ultra-low-power AI hardware design incorporating full-stack optimization can exploit unique features in specific tasks and further minimize power consumption. This thesis presents my research on algorithm-hardware co-design for ultra-low-power hardware for AI applications. Chapter 2 to 5 list my past works. The first work implements a spiking neural network classifier that leverages fully event-driven architecture to reduce power consump-tion while the input activity is low. The second work presents an end-to-end keyword spotting system featuring divisive energy normalization for both internal and external noise robustness. The third work shows a digital in-memory-computing macro utilizing approximate arithmetic hardware for better area and energy efficiency. The last work demonstrates an automatic speech recognition chip featuring bio-inspired neuron model, digital in-memory-computing hardware with time-sharing arithmetic units, and fully pipelined architecture for low power consumption and real-time processing.

No description available.

Smart homes are becoming more popular and there are more and more different devices for smart homes being made. Discussions have increased about the low security level of these devices, how much data is shared with companies that provide these services and how that data is used. This study aims to find what methods are most common for securing smart homes and not sharing too much data, and why these methods are used. The question that the study is based on is: What safety precautions do users take to not spread their private information through devices in smart homes and why? To answer this question a survey has been conducted by letting people answer an online survey and interviews based on the online survey. The answers from the online survey were then subjected to statistical testing, and for the interviews a thematic analysis was made. The most common methods for being safe in smart homes were strong passwords, having different passwords for different services, updating software on devices for smart homes and using multi-factor authentication. During the following interviews the interviewees motivated the reason for using these methods with them being easy to use, convenient and that some services required them. The interviewees also frequently spoke about why they did not use certain methods, which was lack of knowledge about those methods and the associated risks, not having anything to hide and that some methods were too complicated to use.

<p>The rapid expansion of consumer Internet-of-Things (IoT) technology across various application domains has made it one of the most sought-after and swiftly evolving technologies. IoT devices offer numerous benefits, such as enhanced security, convenience, and cost reduction. However, as these devices need access to sensitive aspects of human life to function effectively, their abuse can lead to significant financial, psychological, and physical harm. While previous studies have examined the vulnerabilities of IoT devices, insufficient research has delved into the impact and mitigation of threats to users' privacy and safety. This dissertation addresses the challenge of protecting user safety and privacy against threats posed by IoT device vulnerabilities. We first introduce a novel IWMD architecture, which serves as the last line of defense against unsafe operations of Implantable and Wearable Medical Devices (IWMDs). We demonstrate the architecture's effectiveness through a prototype artificial pancreas. Subsequent chapters emphasize the safety and privacy of smart home device users. First, we propose a unique device activity-based categorization and learning approach for network traffic analysis. Utilizing this technology, we present a new smart home security framework and a device type identification mechanism to enhance transparency and access control in smart home device communication. Lastly, we propose a novel traffic shaping technique that hinders adversaries from discerning user activities through traffic analysis. Experiments conducted on commercially available IoT devices confirm that our solutions effectively address these issues with minimal overhead.</p>

Nowadays, integrated circuits (IC) are mostly implemented using Complementary Metal Oxide Semiconductor (CMOS) transistor technology. This technology has allowed the chip industry to shrink transistors and thus increase the device density, circuit complexity, operation speed, and computation power of the ICs. However, in recent years, the scaling of transistor has faced multiple roadblocks, which will eventually lead the scaling to an end as it approaches physical and economic limits. The dominance of sub-threshold leakage, which slows down the scaling of threshold voltage VTH and the supply voltage VDD, has resulted in high power density on chips. Furthermore, even widely popular solutions such as parallel and multi-core computing have not been able to fully address that problem. These drawbacks have overshadowed the benefits of transistor scaling. With the dawn of Internet of Things (IoT) era, the chip industry needs adjustments towards ultra-low-power circuits and systems. In this thesis, energy-efficient Micro-/Nano-electromechanical (M/NEM) relays are introduced, their non-leaking property and abrupt switch ON/OFF characteristics are studied, and designs and applications in the implementation of ultra-low-power integrated circuits and systems are explored. The proposed designs compose of core building blocks for any functional microprocessor, for instance, fundamental logic gates; arithmetic adder circuits; sequential latch and flip-flop circuits; input/output (I/O) interface data converters, including an analog-to-digital converter (ADC), and a digital-to-analog converter (DAC); system-level power management DC-DC converters and energy management power gating scheme. Another contribution of this thesis is the study of device non-ideality and variations in terms of functionality of circuits. We have thoroughly investigated energy-efficient approximate computing with non-ideal transistors and relays for the next generation of ultra-low-power VLSI systems.

Gartners presenterar External Attack Surface Management (EASM) som är en framväxande cybersäkerhetsdisciplin som identifierar och hanterar de risker som internetbaserade tillgångar och system utgör. Dock är ramverket vagt definierat och har gett författaren intrycket av att fungera som ett komplement till ett mer tekniskt ramverk för säkerhetsövervakning. Syftet med denna studie är att definiera Gartners EASM-ramverket och undersöka om elementen i ramverket har olika vikt av betydelse, samt ifall ramverket behövs omdefinieras för att göra den mer användbar mot IoT-teknologi, specifikt Smart Home. En litteraturstudie har genomförts för att definiera EASM-ramverket och en kvantitativ enkät har skickats elektroniskt och besvarats av åtta olika respondenter för att värdera betydelsen av de olika elementen inom ramverket och om de skulle kunna använda ramverket för Smart Home teknologier inom sina nuvarande organisationer. Respondenterna jobbar inom Smart Homes när denna studie genomfördes och är handplockade på grund av sin erfarenhet och kompetens inom branschen.Respondenterna angav att de olika elementen av EASM-ramverket är av olika vikt och att respondenterna har en osäkerhet om att de skulle använda den nuvarande tillämpningen av EASM-ramverket i sin organisation. Olika faktorer påverkade respondenternas beslut, inklusive deras erfarenhetsnivå, positioner och de företagsstorlekar de arbetar för. Även om de olika elementen i ramverket har olika vikt/betydelse, har elementen ett sekventiellt beroende vilket gör det svårt att ta bort eller byta ut ett element. Analysen tyder på att EASM-ramverket inte är tillräckligt för att vara en komplett försvarslösning inom Smart Homes, utan bör i stället användas tillsammans med Confidentiality, Integrity &amp; Availablity (CIA-triaden) och Autentisering, Auktorisering och Redovisning (AAA-ramverket). Den fysiska aspekten av säkerhet inom Smart Homes behöver också inkluderas för att anpassa EASM-ramverket ytterligare mot Smart Homes.

Fuel consumption of transportation vehicles account for nearly 27% of CO2 emissions from fossil fuel. The environmental impact of of transportation can be lowered with effective ECOfriendly driving. As modern vehicles are equipped with the on-board diagnostics (OBD) system that provides vehicle’s self-diagnostic data which is accessible to from the OBD-II socket in vehicles. The aim of this thesis is to design and implement such a monitor system that consists of an OBD-II reader (containing a Bluetooth communication module) to fetch data from the OBD-II socket and then, via a smartphone, send the data to a cloud server for analysis and visualisation. For this purpose, an ELM327 Bluetooth module (an off-the-shelf OBD-II dongle) was bought, an application has been created for an Android smartphone, and a cloud server has been created using ThinkSpeak (an online solution for cloud data collection and visualisation).   As a result, such monitor system has been implemented at low cost, and then tested and evaluated together with a Toyota Prius driving a round-trip between the Swedish cities of Uppsala and Arlanda. The test results have shown that the system is successful in gathering data from the OBD-II socket and then sending visualizing data. It needs, however, further work to increase the user-friendliness and accuracy of the gathered information from the vehicle. / OBD-II är en internationell standard i fordon som är obligatorisk i moderna bilar möjliggör att med hjälp av hårdvara läsa av information från bilen under färd. Det medför att man kan överföra data så som hastighet, bränsleförbrukning och motortemperaturfrån bilen till en annan tjänst där det presenteras för föraren. Metoden går ut på att transmittera informationen som läses av sensorer i bilen till en internettupkopplad mobiltelefon som för över informationen till en molntjänsst. Datan från bilen ska sedankompletteras med positionsinformation från mobilenhetens GPS enhet. Detta medför att skapandet av en applikation som kan uppfylla målen blir är en central del av projektet. ELM327 är en hårdvarumodul som är designad för att kopplas till ett OBD-II uttag. Modulen kan då läsa av data från CAN bussen i bilen och sedan konverterainformationen till en Bluetooth enhet. En mobiltelefon kan då kommunicera med Bluetooth enheten genom att skapa en Android applikation i utveklarverktyget Androidstudio. Applikationen för sedan över datan till molntjänsten ThingSpeak, som är designat för IoT project. ThingSpeak har en implementering av MatLab, en programmerings plattform för ingenjörer, som låter användaren analysera och visualiseradata i molntjänsten. En begränsning som uppstår är hur mycket pengar som investeras i projetet vilket har inflytande på hur ofta datan kan uppdateras i molntjänsten, vilket påverkar nogrannheten i resultatet. I tesen diskuteras även begränsningarna av systemet och olika utvecklingsmöjligheter av projektet.

The transformation of cities into smart cities is a common occurrence today, and one of the reasons is urbanization. Technology contributes to the ability to deal with new problems that arise. The number of IoT platforms has increased due to their flexibility and value addition regarding interoperability, processing of IoT data, and analysis capability. An IoT platform's capabilities are desirable, not least to municipalities today. Through IoT devices, such as sensors, the municipality can increase their awareness of the city’s surroundings and stay up to date through better insight into trends or new challenges. However, IoT is in its infancy compared to other markets, and there is a limited understanding of the IoT subject in municipal contexts. These aspects contribute to difficulties when municipalities take on trends for smart city initiatives. There is still a lack of design and development guidelines regarding ICT solutions to enable the development of a holistic smart city. The few current smart city deployments also make it challenging to validate which technology should be adopted to achieve the vision for the smart city. Therefore, the study investigates how a central IoT platform might benefit municipal departments in urban development projects. The case study conducted within the City of Stockholm generated ten benefits that might occur if the central IoT platform were available within the municipal departments' urban development projects. The benefits were divided into three themes: ·         Information and data management ·         Reasons to use IoT data ·         Interoperability between the central IoT platform and systems