Embedded systems have been present in our daily lives for some time, but trends clearly show a rise in inter-connectivity in such devices. This presents promising new applications and possibilities, but also opens up a lot attack surface. Our goal in this thesis is to find out how you can develop such interconnected embedded systems in a way that guarantees the three major components of information security: Confidentialy, Integrity and Availability. The main focus of security is networked security. In this thesis, a dual approach is taken: investigate the development process of building secure systems, and perform such an implementation. The artifacts produced as byproducts, the software itself, deployment instructions and lessons learned are all presented. It is shown that the process used helps businesses find a somewhat deterministic approach to security, have a higher level of confidence, helps justify the costs that security work entails and helps in seeing security as a business decision. Embedded systems were also shown to present unforeseen obstacles, such as how the lack of a motherboard battery clashes with X.509. In the end, a discussion is made about how far the system can guarantee information security, what problems still exist and what could be done to mitigate them.

Advances in mobile and pervasive computing, social network technologies and the exponential growth in Internet applications and services will lead to the development of the Internet of Things (IoT). The IoT services will be a key enabling technology to the development of smart infrastructures that will revolutionize the way we do business, manage critical services, and how we secure, protect, and entertain ourselves. Large-scale IoT applications, such as critical infrastructures (e.g., smart grid, smart transportation, smart buildings, etc.) are distributed systems, characterized by interdependence, cooperation, competition, and adaptation. The integration of IoT premises with sensors, actuators, and control devices allows smart infrastructures to achieve reliable and efficient operations, and to significantly reduce operational costs. However, with the use of IoT, we are experiencing grand challenges to secure and protect such advanced information services due to the significant increase in the attack surface. The interconnections between a growing number of devices expose the vulnerability of IoT applications to attackers. Even devices which are intended to operate in isolation are sometimes connected to the Internet due to careless configuration or to satisfy special needs (e.g., they need to be remotely managed). The security challenge consists of identifying accurately IoT devices, promptly detect vulnerabilities and exploitations of IoT devices, and stop or mitigate the impact of cyberattacks. An Intrusion Detection System (IDS) is in charge of monitoring the behavior of protected systems and is looking for malicious activities or policy violations in order to produce reports to a management station or even perform proactive countermeasures against the detected threat. Anomaly behavior detection is a technique that aims at creating models for the normal behavior of the network and detects any significant deviation from normal operations. With the ability to detect new and novel attacks, the anomaly detection is a promising IDS technique that is actively pursued by researchers. Since each IoT application has its own specification, it is hard to develop a single IDS which works properly for all IoT layers. A better approach is to design customized intrusion detection engines for different layers and then aggregate the analysis results from these engines. On the other hand, it would be cumbersome and takes a lot of effort and knowledge to manually extract the specification of each system. So it will be appropriate to formulate our methodology based on machine learning techniques which can be applied to produce efficient detection engines for different IoT applications. In this dissertation we aim at formalizing a general methodology to perform anomaly behavior analysis for IoT. We first introduce our IoT architecture for smart infrastructures that consists of four layers: end nodes (devices), communications, services, and application. Then we show our multilayer IoT security framework and IoT architecture that consists of five planes: function specification or model plane, attack surface plane, impact plane, mitigation plane, and priority plane. We then present a methodology to develop a general threat model in order to recognize the vulnerabilities in each layer and the possible countermeasures that can be deployed to mitigate their exploitation. In this scope, we show how to develop and deploy an anomaly behavior analysis based intrusion detection system (ABA-IDS) to detect anomalies that might be triggered by attacks against devices, protocols, information or services in our IoT framework. We have evaluated our approach by launching several cyberattacks (e.g. Sensor Impersonation, Replay, and Flooding attacks) against our testbeds developed at the University of Arizona Center for Cloud and Autonomic Computing. The results show that our approach can be used to deploy effective security mechanisms to protect the normal operations of smart infrastructures integrated to the IoT. Moreover, our approach can detect known and unknown attacks against IoT with high detection rate and low false alarms.

Advances in mobile and pervasive computing, electronics technology, and the exponential growth in Internet of Things (IoT) applications and services has led to Building Automation System (BAS) that enhanced the buildings we live by delivering more energy-saving, intelligent, comfortable, and better utilization. Through the use of integrated protocols, a BAS can interconnects a wide range of building assets so that the control and management of asset operations and their services can be performed in one protocol. Moreover, through the use of distributed computing and IP based communication, a BAS can implement remote monitor and control in adaptive and real-time manner. However, the use of IoT and distributed computing techniques in BAS are leading to challenges to secure and protect information and services due to the significant increase in the attack surface and the inherent vulnerabilities of BAS integrated protocols. Since there is no intrusion detection and prevention available for BAS network, proposing a reliable security mechanism which can monitor the behavior of BAS assets becomes a major design issue. Anomaly Based Intrusion Detection is a security mechanism that uses baseline model to describe the normal behaviors of a system, so that malicious behaviors occurred in a system can be detected by comparing the observed behavior to the baseline model. With its ability of detecting novel and new attacks, Anomaly based Behavior Analysis (ABA) has been actively pursued by researchers for designing Intrusion Detection Systems. Since the information acquired from a BAS system can be from a variety of sources (e.g. sensors, network protocols, temporal and spatial information), the traditional ABA methodology which merely focuses on analyzing the behavior of communication protocols will not be effective in protecting BAS networks. In this dissertation we aim at developing a general methodology named Context Aware Anomaly based Behavior Analysis (CAABA) which combines Context Awareness technique with Anomaly based Behavior Analysis in order to detect any type of anomaly behaviors occurred in Building Automation Systems. Context Awareness is a technique which is widely used in pervasive computing and it aims at gathering information about a system's environment so it can accurately characterize the current operational context of the BAS network and its services. The CAABA methodology can be used to protect a variety of BAS networks in a sustainable and reliable way. To handle the heterogeneous BAS information, we developed a novel Context Aware Data Structure to represent the information acquired from the sensors and resources during execution of the BAS system which can explicitly describe the system's behavior. By performing Anomaly based Behavior Analysis over the set of context arrays using either data mining algorithm or statistical functions, the BAS baseline models are generated. To validate our methodology, we have applied it to two different building application scenarios: a smart building system which is usually implemented in industrial and commercial office buildings and a smart home system which is implemented in residential buildings, where we have achieved good detection results with low detection errors.

As the vision of the Internet of Things (IoT) becomes a reality, thousands of devices will beconnected to IoT platforms in smart cities and regions. These devices will actively send dataupdates to cloud-based platforms, as part of smart applications in domains like healthcare, trafficand pollution monitoring. Therefore, it is important to study the ability of modern IoT systemsto handle high rates of data updates coming from devices. In this work we evaluated the per-formance of components of the Internet of Things Services Enablement Architecture of theEuropean initiative FIWARE. We developed a testbed that is able to inject data updates usingMQTT and the CoAP-based Lightweight M2M protocols, simulating large scale IoT deploy-ments. Our extensive tests considered the vertical and horizontal scalability of the componentsof the platform. Our results found the limits of the components when handling the load, and thescaling strategies that should be targeted by implementers. We found that vertical scaling is notan effective strategy in comparison to the gains achieved by horizontally scaling the databaselayer. We reflect about the load testing methodology for IoT systems, the scalability needs ofdifferent layers and conclude with future challenges in this topic.

[pt] A cada dia mais e mais brasileiros possuem um telefone celular de última geração com conexão à internet. Estes novos aparelhos são capazes de ler diferentes tipos de etiquetas usadas para armazenar, recuperar e gerenciar informações, e estão conosco em toda parte para apoiar nossas tarefas diárias. Estes pequenos computadores são conscientes de seu entorno, e propícios à comunicação e colaboração com o mundo real. Devido a sua popularidade, disponibilidade e massa crítica de usuários atingida, novos serviços são desenvolvidos baseados no conceito da computação ubíqua, onde computadores e seres humanos são unificados em torno da noção de ambiente. Estes sistemas pervasivos lidam com questões de interação de contexto e reconhecimento de ambientes, e se adaptam de acordo com as preferências do usuário. Nesta dissertação são descritos o desenvolvimento e testes de usabilidade de uma rede social que é fundamentada nos conceitos da computação ubíqua e Internet das Coisas. Esta rede social, dirigida para o tema da enogastronomia, é acessível por dispositivos móveis e utiliza códigos de duas dimensões colados nas garrafas dos vinhos para através do software e da câmera do celular trazer informações de acordo com o contexto do objeto, lugar e preferência do usuário. / [en] Every day more and more Brazilians have a next generation mobile phone with an internet connection. These new devices are able to read different types of labels used to store, retrieve and manage information; they are with us everywhere to support our daily tasks. These small computers are aware of their surroundings and propitious to communication and collaboration with the real world. Due to their popularity, availability and critical mass of users reached, new services are developed based on the concept of ubiquitous computing, where computers and humans are unified around the concept of environment. These systems deal with issues of pervasive interaction of context, recognition of environments and adapt according to user preferences. This thesis presents a description of the development and usability testing of a social network that is based on the concepts of ubiquitous computing and the Internet of Things. This social network, addressed to the theme of enogastronomy, is accessible by mobile devices and uses twodimensional codes pasted on the bottles of wine for using the software and the phone s camera to bring information in accordance with the context of the object, place and user preference.

This master thesis maps contemporary situation linked to the Industry 4.0 topic and sets it into connections and define its relations. The first part is dedicated to describing the beginning and nature of Industry 4.0. Next part shows main national initiatives of several countries. In the other part of thesis there is specific description of terms connected to this concept. Next part is about evaluating benefits, risks and restrictions. After that there is description of present use on market. The last part sums some predictions about Industry 4.0.

We are living in the age of information technology, where we are fully occupied with the revolutionary innovations of the last few decades such as the Internet, mobile devices, wireless communications, social networks, wearables, cloud computing, etc. While these technologies have become integral part of our daily life, we are now anxiously waiting to embrace Internet-of-Things (IoT), intelligent digital assistants, driver-less cars, drone deliveries, virtual reality, and smart city applications. Recently, research community is demonstrating increasing interests about Cyber-Physical Systems (CPS) that resides in the cross-section of embedded systems, network communications, and scalable distributed infrastructures. The main responsibility of a CPS is to collect sensory data about the physical world and to inform the computation module using communication technologies that processes the data, identifies important insights and notifies back using a feedback loop. These notifications can however be control commands to reconfigure the physical world. Such a setup is a useful method to deploy smart city applications. In this dissertation, we keep our focus onto the smart transport objective using vehicular CPS (VCPS) based systems organization. We have compiled this dissertation with our research contributions in this growing field of VCPS. One of our key contributions in this field is an architecture reference model for the cloud-based CPS, C2PS, where we analytically describe the key properties of a CPS: computation, communication and control, while integrating cloud features to it. We have identified various types of computation and interaction modes of this paradigm as well as describe Bayesian network and fuzzy logic based smart connection to select a mode at any time. It is considered that the true adoption of CPS is only possible through the deployment of the IoT systems. Thus, it is important to have IoT as a foundation in the CPS architectures. Our next contribution is to leverage existing Vehicular Adhoc Network (VANET) technologies and map them with the standard IoT-Architecture reference model to design the VCPS, Social Internet-of-Vehicles (SIoV). In this process, we have identified the social structures and system interactions among the subsystems involved in the SIoV. We also present a message structure to facilitate different types of SIoV interactions. The ability of dynamic reconfiguration in a C2PS is very appealing. We capture this feature in the VCPS by designing a model-based reconfiguration scheme for the SIoV, where we measure the data workloads of distinct subsystems involved in various types of SIoV interactions. We further use these models to design dynamic adaptation schemes for the subsystems involved in VCPS interactions. Our final contribution is an application development platform based on C2PS design technique that uses server-client based system communications. In this platform, server side is built using JAVA, client side uses Android, message communication uses JSON and every component has its own MySQL database to store the interactions. We use this platform to emulate and deploy SIoV related applications and scenarios. Such a platform is necessary to continue C2PS related research and developments in the laboratory environment.

Purpose: To investigate possible connections between an Industrial Internet of Things (IIoT) system, such as Predix, and data driven Lean practises. The aim is to examine if an IIoT platform can improve existing practises of Lean, and if so, which Lean tools are most likely influenced and how this is.Design/Methodology: The paper follows a phenomenon-based research approach. The methodology contains of a mix of primary and secondary data. The primary data was obtained through “almost unstructured” interviews with experts, while the secondary data comprises of a comprehensive review of existing literature. Moreover, a model was developed to investigate the connections between the concepts of IIoT and Lean.Findings: Findings derived from expert interviews at General Electric (GE) in Uppsala have led to the conclusion that Predix fulfils the necessary requirements to be considered an IIoT platform. However, the positive effects of the platform on the selected Lean tools could not be found. Only in one instance improved Predix the effectiveness of a Lean tool. Overall, data analytic efforts are performed and let to better in-process control. However, these efforts were independent from the Lean efforts carried out. There was no increase in data collection or analytics due to the Lean initiative and Predix is not utilised for data collection, storage, or analysis. It appears that the pharmaceutical industry is fairly slow in adapting new technologies. Firstly, the high regulatory requirements inherent within the pharmaceutical industry limit the application of cutting edge technology by demanding strict in-process control and process documentation. Secondly, the sheer size of GE itself slows down the adoption of new technology. Lastly, the pragmatic approach of the top management to align the digital strategies of the various industries and thereof resulting allocation of resources to other more technologically demanding businesses hinders the use of Predix at GE in Uppsala.

Context. Internet of Things (IoT) is an extension of the Internet, which now includes physical objects of the real world. The main purpose of Internet of Things is to increase a quality of people’s daily life. A smart home is one of the promising areas in the Internet of Things which increases rapidly. It allows users to control their home devices anytime from any location in the world using Internet connectivity and automate their work based on the physical environment conditions and user preferences. The main issues in deploying the architecture of IoT are the security of the communication between constrained low-power devices in the home network and device performance. Battery lifetime is a key QoS parameter of a battery-powered IoT device which limits the level of security and affects the performance of the communication. These issues have been deepened with the spread of cheap and easy to use microcontrollers which are used by electronic enthusiasts to build their own home automation projects. Objectives. In this study, we investigated wireless communication technologies used in low-power and low-bandwidth home area networks to determine which of them are most suitable for smart home applications. We also investigated the correlation between security, power consumption of constrained IoT device, and performance of wireless communication based on a model of a home automation system with a sensor node. Sensor node was implemented using Arduino Nano microcontroller and RF 433 MHz wireless communication module. Methods. To achieve the stated objectives of this research following methods were chosen: literature review to define common applications and communication technologies used in a smart home scenario and their requirements, comparison of wireless communication technologies in smart home, study of Arduino microcontroller technology, design and simulation of a part of  home automation project based on Arduino, experimental measurements  of execution time and power consumption of Arduino microcontroller with RF 433 MHz wireless module when transmitting data with different levels of security, and analysis of experimental results. Results. In this research, we presented a detailed comparison of ZigBee, WiFi, Bluetooth, Z-Wave, and ANT communication technologies used in a smart home in terms of the main characteristics. Furthermore, we considered performance, power consumption, and security. A model of a home automation system with a sensor node based on Arduino Nano was described with sleep management and performance evaluation. The results show that the battery lifetime of Arduino in a battery-powered sensor node scenario is determined by the communication speed, sleep management, and affected by encryption. Conclusions. The advanced communication strategy can be used to minimize the power consumption of the device and increase the efficiency of the communication. In that case, our security measures will reduce the productivity and lifetime of the sensor node not significantly. It’s also possible to use symmetric encryption with smaller block size.

The goal of the thesis is to provide investors and established businesses insights into the evolving concept of Internet of Things in the context of a business opportunity. First, the thesis provides comprehensive overview of the IoT concept, its historical development and relevant concepts similar to IoT including its definition and explanation. Second, the thesis discusses IoT as a disruptive technology with implications for general business strategy, current business models, value chains and competitive landscape. Third, it describes overwhelming opportunities for IoT application in various business fields and processes bringing added value to its stakeholders. Visionary concepts and applicable use cases are identified. Finally, the thesis analyses IoT market perception from both customer and business perspective based on quantitative and qualitative data researched. The research is focused mainly on customer awareness and value perception of IoT products as well as major drivers and challenges of the IoT market from business players' perspective. Such analytical insights identify major patterns and dynamism of the IoT market.