The Industrial Internet of Things (IIoT) is growing day by day and is implemented in many industries. The centralized architecture of an IIoT system is composed of several devices that communicate with a special device only via one link, in an instance where this one link is attacked, major problems could occur for the whole system. The solution is to decentralize the entire architecture, a feature that the implementation of blockchain technology provides. Blockchain technology uses numerous consensus algorithms and some of the consensus algorithms require a large amount of computational power , such as the proof of work consensus algorithm. The problem is that IIoT devices have limited processor performance therefore it is important to find consensus algorithms that are suitable for an IIoT system in terms of time efficiency and electricity consumption. The question then becomes, which of the following different consensus algorithms; proof of work, proof of stake and proof of authentication performs best in an IIoT environment in terms of time efficiency and electricity consumption?  This question can be answered by implementing blockchain technology using the three aforementioned consensus algorithms in an IIoT environment to see which consensus algorithm is the most time efficient and uses the smallest amount of electricity. The results showed that proof of stake was the best consensus algorithm both in terms of time efficiency and electricity consumption. / Sakernas internet inom industrin (IIoT) växer dag för dag och används i flertalet industrier. Den centraliserade arkitekturen av ett IIoT-system består av flera enheter som kommunicerar med en speciell enhet endast via en länk och detta kan skapa stora problem för hela systemet om endast denna länk attackeras. Lösningen är att decentralisera hela arkitekturen, en funktion som implementeringen av blockkedjeteknologi förser. Inom blockkedjeknologi används flertalet algoritmer och bland algoritmerna finns det flera som kräver hög processorprestanda, som t.ex proof of work algoritmen. Problemet är att IIoT-enheter har begränsad processorprestanda, och ett viktigt skäl är att hitta algoritmer som är anpassade för ett IIoT-system beträffande tidseffektivitet samt elkonsumtion. Frågan blir då, vilken av de olika konsensus algoritmerna; proof of work, proof of stake och proof of authentication presterar bäst i en IIoT-miljö sett ur tidseffektivitet och elkonsumtion?  Denna fråga kan besvaras genom att implementera blockkedjeteknologi med de tre ovannämnda algoritmer i en IIoT-miljö för att se vilken algoritm är den mest tidseffektiva och har lägst elkonsumtion. Resultatet visade att proof of stake var den bästa konsensus algoritmen både tidsmässigt och elkonsumtion mässigt.

I detta examensarbete analyseras Purduemodellen och dess tillämplighet inomnätverkssäkerhet för industriella styrsystem inom ramarna för Industri 4.0. Genomen litteraturstudie granskas modellens struktur och funktion i relation till de nyautmaningarna som uppkommit genom ökad digitalisering och integrering av IIoTteknologier. Studien identifierar både styrkor och svagheter i den traditionellaPurduemodellen. I resultatavsnittet introduceras en modifierad version avPurduemodellen, utformad för att förstärka nätverkssäkerheten och öka systemensförmåga att hantera cyberhot samt anpassa sig till teknologiska förändringar i denindustriella sektorn. Denna anpassning har genomförts genom införandet avytterligare säkerhetsstandarder och verktyg i syfte att förbättra modellenseffektivitet och relevans. / In this thesis, the Purdue model and its applicability within network security forindustrial control systems under the framework of Industry 4.0 are analyzed.Through a literature review, the model's structure and function are examined inrelation to the new challenges that have emerged due to increased digitization andintegration of IIoT technologies. The study identifies both strengths and weaknessesin the traditional Purdue model. In the results section, a modified version of thePurdue model is introduced, designed to enhance network security and increase thesystems' ability to handle cyber threats and adapt to technological changes in theindustrial sector. This adaptation has been achieved by incorporating additionalsecurity standards and tools aimed at improving the model's efficiency andrelevance.

This thesis details the design of a protocol translator between the industrial-automation protocol OPC UA, and HTTP. The design is based on the architecture of the protocol translator of the Arrowhead framework, and is interoperable with all of its associated protocols. The design requirements are defined to comply with a service-oriented architecture (SOA) and RESTful interaction through HTTP, with minimal requirement of the consuming client to be familiar with OPC UA semantics. Effort is put into making translation as transparent as possible, but limits the scope of this work to exclude a complete semantic translation. The solution presented in this thesis satisfies structural- and foundational interoperability, and bridges interaction to be independent of OPC UA services. The resulting translator is capable of accessing the content of any OPC UA server with simple HTTP-requests, where addressing is oriented around OPC UA nodes.

Every day, more and more devices are getting connected to the Internet and becoming what we know as the Internet of Things (IoT). In both commercial and industrial context, IoT plays a significant role in enabling automatisation and connectivity. For companies that want to become the innovation leader in their branch of industry, IoT is a useful method to gain competitive advantage where automatisation, predictive maintenance and connectivity can improve company’s performance. However, no research have been done from the perspective of an IoT-provider. How they can fully harness the power of IoT when they adopt it for their existing products or services? This study aim to investigate how a theoretical model would look like with the performance impact in focus when an innovation-driven company adopt IoT on their existing products. The research is conducted with a case study of a Swedish company in the heavy industry sector, which has successfully adapted IoT into their products. The empirical data was collected through documentation review and interview. This study results in a conceptual model that contains crucial factors which needs to be taken into consideration when adopting IoT. However, further research needs to be done, in order to verify this model as well as to be able to generalise the findings to cover innovation adoption in general.

Internet of Things (‘IoT’) systems are complex, asynchronous solutions often comprised of various software and hardware components developed in isolation of each other. These components function with different degrees of reliability and performance over an inherently unreliable network, the Internet. Many IoT systems are developed within silos that do not provide the ability to communicate or be interoperable with other systems and platforms. Literature exists on how these systems should be designed, how they should interoperate, and how they could be improved, but practice does not always consult literature. The work brings together a proposed reference architecture for the IoT and engineering practices for flow semantics found in existing literature with a commercial implementation of an IoT platform. It demonstrates that the proposed IoT reference architecture and flow-service-quality engineering practices when integrated together can produce a more robust system with increased functionality and interoperability. It shows how such practices can be implemented into a commercial solution, and explores the value provided to the system when implemented. This work contributes to the current understanding of how complex IoT systems can be developed to be more reliable and interoperable using reference architectures and flow semantics. The work highlights the value of integration of academic solutions with commercial implementations of complex systems.

In this new digital age, efficiency, quality and competition are all increasing rapidly as companies leverage the Industrial Internet of Things (IIoT). However, while industrial innovation moves at a faster and faster pace, educational institutions have lagged in the development of the curriculum and environment needed to support further development of the IIoT. To fully realize the potential of the IIoT in the manufacturing sector educational institutions must support the technological training and education rigor demanded to instill the skills and thought leadership to move the industry forward. The purpose of this research is to provide an IIoT core system in an educational factory environment. This system will assist in teaching basic principles of IIoT in the factory while simultaneously allowing for students to envision the manufacturing journey of any facility by implementing principles of IIoT. This will be accomplished by providing all the following capabilities together in a single data system: unified connectivity, role-based data display, real-time issue identification, data analytics, and augmented reality.

Presented diploma thesis is focused on the implementation of Wireless M-Bus protocol to embedded device RaspberryPi with expansion board UniPi. The protocol is implemented in Python with Wireless M-Bus devices communicating via IQRF transceiver connected to the UART bus. The theoretical part is focused on an overview of embedded devices for the IoT, the possibility of their expansion. Further, the UniPi expansion board and Wireless M-Bus transceiver are detailed. First part of the thesis focuses on the Wireless M-bus layers, which provides a basic knowledge for understanding the practical part. The theoretical part concludes overview of captured devices including a description of their data units. In the practical part is the implementation of the sample application for receriving data from a Wireless M-Bus sensors. The application is able to read data from devices transmitting encrypted communication.

The use of Internet-of-Things (IoT) makes it possible to inter-connect Information Technology (IT) and Operational Technology (OT) into a completely new system. This convergence is often known as Industrial IoT (IIoT). IIoT brings a lot of benefits to industrial assets, such as improved efficiency and productivity, reduced cost, and depletion of human error. However, the high inter-connectivity opens new possibilities for cyber incidents. These incidents can cause major damage like halting of production on the manufacturing line, or catastrophic havoc to companies, communities, and countries causing power outages, floods, and fuel shortages. Such incidents are important to be predicted, stopped, or alleviated at no cost. Moreover, these incidents are a great motive for researchers and practitioners to investigate known security problems and find potential moderation strategies.  In this thesis work, we try to identify what types of IIoT systems have been investigated in the literature. We seek out to find if software-related issues can yield security problems. Also, we make an effort to perceive what are the proposed methods to mitigate the security threats.We employ the systematic literature review (SLR) methodology to collect this information. The results are gathered from papers published in the last five years and they show an increased interest in research in this domain. We find out software vulnerabilities are a concern for IIoT systems, mainly firmware vulnerabilities and buffer overflows, and there are a lot of likely attacks that can cause damage, mostly injection and DDoS attacks. There are a lot of different solutions which offer the possibility to stop the identified problems and we summarize them. Furthermore, the research gap considering the update process in these systems and devices, as well as a problem with the unsupervised software supply chain is identified.

I den fluktuerande digitaliseringsvågen har den fjärde industriella revolutionen eller Industry 4.0 initierat inom tillverkningsindustrin vilket påskyndar företag att anpassa och förändra hela verksamheter för att vara fortsatt konkurrenskraftiga. Industrial Internet of Things (IIoT) har blivit en central del av denna förändring för tillverkningsföretag och kan förklaras som företag som utnyttjar enheter för att samla data i realtid och i sin tur gå mer mot den smarta fabriken. En rad olika möjligheter kan genomföras för industrier med uppgången av IIoT, även om framgången med denna förändring kan variera mellan olika företag beroende på storlek, resurser och ekonomisk stabilitet. Parallellt med möjligheterna uppstår även utmaningar för företag, särskilt små och medelstora företag, då dessa saknar ekonomiska resurser och storlek för att kunna omfördela och omvandla sin verksamhet. I denna studie har målet varit att skildra hur medelstora tillverkningsföretag hanterar implementeringen av IIoT och den smarta fabriken för att anpassa sig till det ständigt föränderliga tekniska paradigm som Industry 4.0 har introducerat. Slutsatser har dragits utifrån kombinationen av en teoretisk ram och intervjuer med sex svenska medelstora tillverkningsföretag. Digitaliseringsstrategier för tillverkningsföretag varierar beroende på bransch. Det finns emellertid enighet om att insatser för en digitaliserad produktion måste ske för att förbli konkurrenskraftig där automatisering, övervakning och kontroll av processer inom IIoT är nyckelfaktorer för att förbli konkurrenskraftiga. Tidsplanen och implementeringsnivån kan också variera beroende på digital kompetens och motståndskraft mot förändring från personalen. Viktigt att poängtera är att sambandet mellan IIoT, digitalisering och ökad konkurrenskraft inte är de enda faktorerna som krävs utan det finns fler faktorer att beakta. Studien pekar även på att konkurrensfördelar sällan är det främsta skälet till att företag väljer att digitalisera och implementera IIoT. / In the fluctuating wave of digitization, the fourth industrial revolution or Industry 4.0 in the manufacturing industry, has begun that has accelerated industries and companies to adapt and change their whole business to maintain competitive. Industrial Internet of Things (IIoT) has become a central part of this change for manufacturing companies and can be interpreted as companies taking advantage of units to gather real-time data and in turn, lean towards the smart factory. A range of possibilities can be accessed by industries with the rise of IIoT, though the success of this change can differ between different companies depending on size, resources, and economic stability. Parallel to the opportunities, challenges arises for companies, especially small and middle-sized enterprises, that lack the economic resources and scale to redistribute and transform their business. In this paper, the goal has been to distinguish how middle-sized manufacturing companies handle the implementation of IIoT and the smart factory in order to adapt to the ever-changing technical paradigm that Industry 4.0 has introduced. Conclusions have been drawn from the combination of a theoretical framework and interviews with six Swedish middle-sized manufacturing companies. The digitization strategy for manufacturing companies varies from industries. However, there is a consensus that efforts towards a digitized production must take place in order to stay competitive where automation-, monitoring-, and controlling processes within IIoT are main factors to stay competitive. The pace and level of implementation can also differ depending on digital qualification and resistance to change from the staff. Important to note is that the relation between IIoT, digitization and increased competitiveness is not the only factors that are significant as there are more things to consider. The study also shows that competitive advantages are rarely the main reason why companies choose to digitize and implement IIoT.

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