The existing closed-loop sensor networks are based on architectures that are designed and implemented for one specific application and require dedicated sensing and computational resources. This prevents the sharing of these networks. In this work, we propose an architecture of virtualization to allow sharing of closed-loop sensor networks. We also propose a scheduling approach that will manage requests from competing applications and evaluate their impact on system utilization against utilization achieved by more traditional, dedicated sensor networks. These algorithms are evaluated through trace-driven simulations, where the trace data is taken from CASA’s closed-loop weather radar sensor network. Results from this evaluation show that the proposed scheduling algorithms applied in a shared network result in cost savings, that are the result of being able to multiplex applications onto a single network as opposed to running each application on an dedicated sensor network.

Endpoint devices are integral in the realisation of any industrial cyber-physical system (ICPS) application. As part of the work of promoting safer and more secure industrial Internet of Things (IIoT) networks and devices, the Industrial Internet Consortium (IIC) and the OpenFog Consortium have developed security framework specifications detailing security techniques and technologies that should be employed during the design of an IIoT network. Previous work in establishing cryptographic services on platforms intended for wireless sensor networks (WSN) and the Internet of Things (IoT) has concluded that security mechanisms cannot be implemented using software libraries owing to the lack of memory and processing resources, the longevity requirements of the processor platforms, and the hard real-time requirements of industrial operations. Over a decade has passed since this body of knowledge was created, however, and IoT processors have seen a vast improvement in the available operating and memory resources while maintaining minimal power consumption. This study aims to update the body of knowledge regarding the provision of security services on an IoT platform by conducting a detailed analysis regarding the performance of new generation IoT platforms when running software cryptographic services. The research considers execution time, power consumption and memory occupation and works towards a general, implementable design of a secure, IIoT edge device. This is realised by identifying security features recommended for IIoT endpoint devices; identifying currently available security standards and technologies for the IIoT; and highlighting the trade-offs that the application of security will have on device size, performance, memory requirements and monetary cost. / Dissertation (MSc)--University of Pretoria, 2017. / Electrical, Electronic and Computer Engineering / MSc / Unrestricted

Smartness of technical systems relies also on appropriate actuators and sensors. Different to the prevalent definition of smartness to be embedded machine intelligence, in this paper elegance and simplicity of solutions is postulated be a more uniform and useful characterization. This is discussed in view of the current trends towards cyber physical systems and the role of components and subsystems, as well as of models for their effective realization. Current research on actuators and sensing in the fluid power area has some emphasis on simplicity and elegance of solution concepts and sophisticated modeling. This is demonstrated by examples from sensorless positioning, valve actuation, and compact hydraulic power supply.

Cyberattacks against critical infrastructures has been a growing problem for the past couple of years. These infrastructures are a particularly desirable target for adversaries, due to their vital importance in society. For instance, a stop in the operation of a critical infrastructure could result in a crippling effect on a nation's economy, security or public health. The reason behind this increase is that critical infrastructures have become more complex, often being integrated with a large network of various cyber components. It is through these cyber components that an adversary is able to access the system and conduct their attacks. In this thesis, we consider methods which can be used as a first line of defence against such attacks for Cyber-Physical Systems (CPS). Specifically, we start by studying how information leaks about a system's dynamics helps an adversary to generate attacks that are difficult to detect. In many cases, such attacks can be detrimental to a CPS since they can drive the system to a breaking point without being detected by the operator that is tasked to secure the system. We show that an adversary can use small amounts of data procured from information leaks to generate these undetectable attacks. In particular, we provide the minimal amount of information that is needed in order to keep the attack hidden even if the operator tries to probe the system for attacks.  We design defence mechanisms against such information leaks using the Hammersley-Chapman-Robbins lower bound. With it, we study how information leakage could be mitigated through corruption of the data by injection of measurement noise. Specifically, we investigate how information about structured input sequences, which we call events, can be obtained through the output of a dynamical system and how this leakage depends on the system dynamics. For example, it is shown that a system with fast dynamical modes tends to disclose more information about an event compared to a system with slower modes. However, a slower system leaks information over a longer time horizon, which means that an adversary who starts to collect information long after the event has occured might still be able to estimate it. Additionally, we show how sensor placements can affect the information leak. These results are then used to aid the operator to detect privacy vulnerabilities in the design of a CPS. Based on the Hammersley-Chapman-Robbins lower bound, we provide additional defensive mechanisms that can be deployed by an operator online to minimize information leakage. For instance, we propose a method to modify the structured inputs in order to maximize the usage of the existing noise in the system. This mechanism allows us to explicitly deal with the privacy-utility trade-off, which is of interest when optimal control problems are considered. Finally, we show how the adversary's certainty of the event increases as a function of the number of samples they collect. For instance, we provide sufficient conditions for when their estimation variance starts to converge to its final value. This information can be used by an operator to estimate when possible attacks from an adversary could occur, and change the CPS before that, rendering the adversary's collected information useless. / De senaste åren har cyberanfall mot kritiska infrastructurer varit ett växande problem. Dessa infrastrukturer är särskilt utsatta för cyberanfall, eftersom de uppfyller en nödvändig function för att ett samhälle ska fungera. Detta gör dem till önskvärda mål för en anfallare. Om en kritisk infrastruktur stoppas från att uppfylla sin funktion, då kan det medföra förödande konsekvenser för exempelvis en nations ekonomi, säkerhet eller folkhälsa. Anledningen till att mängden av attacker har ökat beror på att kritiska infrastrukturer har blivit alltmer komplexa eftersom de numera ingår i stora nätverk dör olika typer av cyberkomponenter ingår. Det är just genom dessa cyberkomponenter som en anfallare kan få tillgång till systemet och iscensätta cyberanfall. I denna avhandling utvecklar vi metoder som kan användas som en första försvarslinje mot cyberanfall på cyberfysiska system (CPS). Vi med att undersöka hur informationsläckor om systemdynamiken kan hjälpa en anfallare att skapa svårupptäckta attacker. Oftast är sådana attacker förödande för CPS, eftersom en anfallare kan tvinga systemet till en bristningsgräns utan att bli upptäcka av operatör vars uppgift är att säkerställa systemets fortsatta funktion. Vi bevisar att en anfallare kan använda relativt små mängder av data för att generera dessa svårupptäckta attacker. Mer specifikt så härleder ett uttryck för den minsta mängd information som krävs för att ett anfall ska vara svårupptäckt, även för fall då en operatör tar till sig metoder för att undersöka om systemet är under attack. I avhandlingen konstruerar vi försvarsmetoder mot informationsläcker genom Hammersley-Chapman-Robbins olikhet. Med denna olikhet kan vi studera hur informationsläckan kan dämpas genom att injicera brus i datan. Specifikt så undersöker vi hur mycket information om strukturerade insignaler, vilket vi kallar för händelser, till ett dynamiskt system som en anfallare kan extrahera utifrån dess utsignaler. Dessutom kollar vi på hur denna informationsmängd beror på systemdynamiken. Exempelvis så visar vi att ett system med snabb dynamik läcker mer information jämfört med ett långsammare system. Däremot smetas informationen ut över ett längre tidsintervall för långsammare system, vilket leder till att anfallare som börjar tjuvlyssna på ett system långt efter att händelsen har skett kan fortfarande uppskatta den. Dessutom så visar vi jur sensorplaceringen i ett CPS påverkar infromationsläckan. Dessa reultat kan användas för att bistå en operatör att analysera sekretessen i ett CPS. Vi använder även Hammersley-Chapman-Robbins olikhet för att utveckla försvarslösningar mot informationsläckor som kan användas \textit{online}. Vi föreslår modifieringar till den strukturella insignalen så att systemets befintliga brus utnyttjas bättre för att gömma händelsen. Om operatören har andra mål den försöker uppfylla med styrningen så kan denna metod användas för att styra avvängingen mellan sekretess och operatorns andra mål. Slutligen så visar vi hur en anfallares uppskattning av händelsen förbättras som en funktion av mängden data får tag på. Operatorn kan använda informationen för att ta reda på när anfallaren kan tänka sig vara redo att anfalla systemet, och därefter ändra systemet innan detta sker, vilket gör att anfallarens information inte längre är användbar. / <p>QC 20210820</p>

Esta investigación doctoral aborda la robótica asistencial (Assistive Robotics) como tema general, también llamada robótica social; específicamente el estudio de la interacción de la relación humano-robot. Con base en el estudio del estado del arte realizado, esta tesis se orientó hacia el siguiente problema de investigación: ¿es posible mejorar la efectividad terapéutica y de esta forma la calidad de vida de las personas con dificultades para comunicarse verbalmente debido a singularidades relacionadas con el habla y lenguaje; por medio del desarrollo de estrategias socio-terapéuticas que utilicen robots y mundos virtuales con frecuencias de exposición flexibles en comparación con la exposición programada utilizando únicamente robots en el mundo físico? El problema de investigación brinda una direccionalidad innovadora desde varias perspectivas científicas. Por un lado, la integración terapéutica de recursos en el mundo virtual así como en el mundo físico con robótica asistencial en colaboración con el ser humano para cumplir un objetivo de crecimiento personal. Además, la posibilidad de romper la barrera del tiempo controlado de exposición terapéutica por medio de la tecnología. Y, por otro lado, metodológicamente buscar un abordaje científico que demuestre causalidad y no sólo asociación por medios cualitativos; dado que se quiere saber si la efectividad terapéutica realmente puede incrementar como variable de respuesta. Por lo tanto, y como elemento de innovación adicional, esta investigación abordó el diseño de un prototipo tecnológico de programación robótica con emulación animada, que integra el uso de un avatar robótico virtual para facilitar la interacción social de personas que presentan dificultades de comunicación verbal relacionadas con el habla y lenguaje. El objetivo general de esta tesis se plantea como sigue: “Aportar al conocimiento científico sobre la interacción humano-robot con fines terapéuticos de comunicación verbal en el idioma castellano comparando el uso de robots en el mundo físico y virtual con flexibilidad de tiempos versus la interacción limitada a robots físicos por periodos de tiempo fijos para saber si es posible incrementar de forma relevante la efectividad terapéutica en términos de mejora de habilidades y tiempo invertido en terapia.” Esta investigación contribuye científicamente con la propuesta de un enfoque metodológico que busca obtener resultados basados en la evidencia experimental y no sólo en el análisis hermenéutico o el análisis léxico de datos cualitativos que constituye lo más frecuente en la investigación científica en este campo. En este sentido, el método exploratorio basado en datos cualitativos y abordajes epistemológicos subjetivistas pueden verse bien complementados con investigación positivista más orientada a la evidencia basada en resultados vinculados a la causalidad. Otra aportación de esta investigación está en el desarrollo tecnológico orientado hacia el uso de la experiencia de realidad virtual de personas con condiciones de limitación en habla o lenguaje en combinación con un robot físico. Esta es una forma innovadora de buscar la exposición continua y en tiempo real a los protocolos de terapia de habla sin supervisión física del terapeuta, teniendo en cuenta que las aplicaciones robóticas en mundos virtuales vinculados con el "mundo físico" no son frecuentes.

This thesis investigates the possibility of connecting an embedded device, STM32 B-L4S5I-IOT01A IoT discovery node, to a Eclipse Arrowhead framework local cloud.This thesis also examines the benefits of using the Eclipse Arrowhead framework compared to its competitors Amazon Web Services and Microsoft Azure. The world is entering a new industrial revolution, often referred to as Industry 4.0, moving towards a more decentralized and software-oriented means of production.This fourth industrial revolution incorporates System of Systems, Cyber-Physical Systems, and embedded software technologies. One of the internet-based industrial solutions is the Eclipse Arrowhead framework. The Eclipse Arrowhead framework contains many examples in various promgramming languages and technologies but lacks an example of a specific piece of hardware connecting to a local Eclipse Arrowhead cloud.Therefore, a project with the clear intent to showcase both the capabilities and possibilities of Cyber-Physical systems and the Eclipse Arrowhead framework is needed. The system this thesis implements consists of three major parts: the stm32 board, a Python flask app, and the Eclipse Arrowhead framework.The main objective of the Eclipse Arrowhead framework is to connect the consumer and the provider in a safe and structured way.The provider is built with C/C++ using ARMs' mbed os.  The response time of the different frameworks, Eclipse Arrowhead framework and Amazon Web Services, was measured.We made a thousand attempts to form an adequate basis for an average response time. In addition to presenting the average response time, we calculated the maximum and minimum response times to understand the different frameworks' performance further.  The thesis shows some benefits in response time when running an Eclipse Arrowhead framework local cloud instead of using a remote service such as Amazon Web Services. Average response time decreased by 17.5 times while running an Eclipse Arrowhead framework local cloud.Maximum and minimum response times decreased by 1.9 and 134 times, respectively.

The main purpose of this dissertation is to define and solve problems on optimal sensing and actuating policies in Cyber-Physical Systems (CPSs). Cyber-physical system is a term that was introduced recently to define the increasing complexity of the interactions between computational hardwares and their physical environments. The problem of designing the ``cyber'' part may not be trivial but can be solved from scratch. However, the ``physical'' part, usually a natural physical process, is inherently given and has to be identified in order to propose an appropriate ``cyber'' part to be adopted. Therefore, one of the first steps in designing a CPS is to identify its ``physical'' part. The ``physical'' part can belong to a large array of system classes. Among the possible candidates, we focus our interest on Distributed Parameter Systems (DPSs) whose dynamics can be modeled by Partial Differential Equations (PDE). DPSs are by nature very challenging to observe as their states are distributed throughout the spatial domain of interest. Therefore, systematic approaches have to be developed to obtain the optimal locations of sensors to optimally estimate the parameters of a given DPS. In this dissertation, we first review the recent methods from the literature as the foundations of our contributions. Then, we define new research problems within the above optimal parameter estimation framework. Two different yet important problems considered are the optimal mobile sensor trajectory planning and the accuracy effects and allocation of heterogeneous sensors. Under the remote sensing setting, we are able to determine the optimal trajectories of remote sensors. The problem of optimal robust estimation is then introduced and solved using an interlaced ``online'' or ``real-time'' scheme. Actuation policies are introduced into the framework to improve the estimation by providing the best stimulation of the DPS for optimal parameter identification, where trajectories of both sensors and actuators are optimized simultaneously. We also introduce a new methodology to solving fractional-order optimal control problems, with which we demonstrate that we can solve optimal sensing policy problems when sensors move in complex media, displaying fractional dynamics. We consider and solve the problem of optimal scale reconciliation using satellite imagery, ground measurements, and Unmanned Aerial Vehicles (UAV)-based personal remote sensing. Finally, to provide the reader with all the necessary background, the appendices contain important concepts and theorems from the literature as well as the Matlab codes used to numerically solve some of the described problems.

This dissertation presents the design, simulation, and execution of multi-unmanned aerial vehicles (UAV)-based cooperative source seeking and contour mapping with cyber-physical systems(CPS). Both fixed-wing UAVs and vertical takeoff and landing (VTOL) UAVs are developed as the flight platforms. Compared with single UAV, multi-UAV formation with advanced cooperative control strategies has more advantages for radiative source detection, especially in urgent tasks, for example, detecting nuclear radiation before deploying the salvage. A contour mapping algorithm for the nuclear radiation is proposed, and practical predefined waypoint-based formation flights are realized. Next, four scenarios are developed for multi-UAV-based cooperative source seeking and contour mapping of radiative signal fields. the fixed wing UAVs are more suitable for widespread detection, while VTOL UAVs are better for accurate detection. The flight control of each VTOL UAV is very critical, and the designed fractional order controller for pitch-loop control guarantees the stable flight. The conclusion of this dissertation and suggestions for future research are presented in the end.

Les Systèmes Cyber Physiques (CPS) intègrent des composants programmables afin de contrôler un processus physique. Ils sont désormais largement répandus dans différentes industries comme l’énergie, l’aéronautique, l’automobile ou l’industrie chimique. Parmi les différents CPS existants, les systèmes SCADA (Supervisory Control And Data Acquisition) permettent le contrôle et la supervision des installations industrielles critiques. Leur dysfonctionnement peut engendrer des impacts néfastes sur l’installation et son environnement.Les systèmes SCADA ont d’abord été isolés et basés sur des composants et standards propriétaires. Afin de faciliter la supervision du processus industriel et réduire les coûts, ils intègrent de plus en plus les technologies de communication et de l’information (TIC). Ceci les rend plus complexes et les expose à des cyber-attaques qui exploitent les vulnérabilités existantes des TIC. Ces attaques peuvent modifier le fonctionnement du système et nuire à sa sûreté.On associe dans la suite la sûreté aux risques de nature accidentelle provenant du système, et la sécurité aux risques d’origine malveillante et en particulier les cyber-attaques. Dans ce contexte où les infrastructures industrielles sont contrôlées par les nouveaux systèmes SCADA, les risques et les exigences liés à la sûreté et à la sécurité convergent et peuvent avoir des interactions mutuelles. Une analyse de risque qui couvre à la fois la sûreté et la sécurité est indispensable pour l’identification de ces interactions ce qui conditionne l’optimalité de la gestion de risque.Dans cette thèse, on donne d’abord un état de l’art complet des approches qui traitent la sûreté et la sécurité des systèmes industriels et on souligne leur carences par rapport aux quatre critères suivants qu’on juge nécessaires pour une bonne approche basée sur les modèles : formelle, automatique, qualitative et quantitative, et robuste (i.e. intègre facilement dans le modèle des variations d’hypothèses sur le système).On propose ensuite une nouvelle approche orientée modèle d’analyse conjointe de la sûreté et de la sécurité : S-cube (SCADA Safety and Security modeling), qui satisfait les critères ci-dessus. Elle permet une modélisation formelle des CPS et génère l’analyse de risque qualitative et quantitative associée. Grâce à une modélisation graphique de l’architecture du système, S-cube permet de prendre en compte différentes hypothèses et de générer automatiquement les scenarios de risque liés à la sûreté et à la sécurité qui amènent à un évènement indésirable donné, avec une estimation de leurs probabilités.L’approche S-cube est basée sur une base de connaissance (BDC) qui décrit les composants typiques des architectures industrielles incluant les systèmes d’information, le contrôle et la supervision, et l’instrumentation. Cette BDC a été conçue sur la base d’une taxonomie d’attaques et modes de défaillances et un mécanisme de raisonnement hiérarchique. Elle a été mise en œuvre à l’aide du langage de modélisation Figaro et ses outils associés. Afin de construire le modèle du système, l’utilisateur saisit graphiquement l’architecture physique et fonctionnelle (logiciels et flux de données) du système. L’association entre la BDC et ce modèle produit un modèle d’états dynamiques : une chaîne de Markov à temps continu. Pour limiter l’explosion combinatoire, cette chaîne n’est pas construite mais peut être explorée de deux façons : recherche de séquences amenant à un évènement indésirable ou simulation de Monte Carlo, ce qui génère des résultats qualitatifs et quantitatifs.On illustre enfin l’approche S-cube sur un cas d’étude réaliste : un système de stockage d’énergie par pompage, et on montre sa capacité à générer une analyse holistique couvrant les risques liés à la sûreté et à la sécurité. Les résultats sont ensuite analysés afin d’identifier les interactions potentielles entre sûreté et sécurité et de donner des recommandations. / Cyber physical systems (CPS) denote systems that embed programmable components in order to control a physical process or infrastructure. CPS are henceforth widely used in different industries like energy, aeronautics, automotive, medical or chemical industry. Among the variety of existing CPS stand SCADA (Supervisory Control And Data Acquisition) systems that offer the necessary means to control and supervise critical infrastructures. Their failure or malfunction can engender adverse consequences on the system and its environment.SCADA systems used to be isolated and based on simple components and proprietary standards. They are nowadays increasingly integrating information and communication technologies (ICT) in order to facilitate supervision and control of the industrial process and to reduce exploitation costs. This trend induces more complexity in SCADA systems and exposes them to cyber-attacks that exploit vulnerabilities already existent in the ICT components. Such attacks can reach some critical components within the system and alter its functioning causing safety harms.We associate throughout this dissertation safety with accidental risks originating from the system and security with malicious risks with a focus on cyber-attacks. In this context of industrial systems supervised by new SCADA systems, safety and security requirements and risks converge and can have mutual interactions. A joint risk analysis covering both safety and security aspects would be necessary to identify these interactions and optimize the risk management.In this thesis, we give first a comprehensive survey of existing approaches considering both safety and security issues for industrial systems, and highlight their shortcomings according to the four following criteria that we believe essential for a good model-based approach: formal, automatic, qualitative and quantitative and robust (i.e. easily integrates changes on system into the model).Next, we propose a new model-based approach for a safety and security joint risk analysis: S-cube (SCADA Safety and Security modeling), that satisfies all the above criteria. The S-cube approach enables to formally model CPS and yields the associated qualitative and quantitative risk analysis. Thanks to graphical modeling, S-cube enables to input the system architecture and to easily consider different hypothesis about it. It enables next to automatically generate safety and security risk scenarios likely to happen on this architecture and that lead to a given undesirable event, with an estimation of their probabilities.The S-cube approach is based on a knowledge base that describes the typical components of industrial architectures encompassing information, process control and instrumentation levels. This knowledge base has been built upon a taxonomy of attacks and failure modes and a hierarchical top-down reasoning mechanism. It has been implemented using the Figaro modeling language and the associated tools. In order to build the model of a system, the user only has to describe graphically the physical and functional (in terms of software and data flows) architectures of the system. The association of the knowledge base and the system architecture produces a dynamic state based model: a Continuous Time Markov Chain. Because of the combinatorial explosion of the states, this CTMC cannot be exhaustively built, but it can be explored in two ways: by a search of sequences leading to an undesirable event, or by Monte Carlo simulation. This yields both qualitative and quantitative results.We finally illustrate the S-cube approach on a realistic case study: a pumped storage hydroelectric plant, in order to show its ability to yield a holistic analysis encompassing safety and security risks on such a system. We investigate the results obtained in order to identify potential safety and security interactions and give recommendations.

The operation of the smart grid is expected to be heavily reliant on microprocessor-based control. Thus, there is a strong need for interoperability standards to address the heterogeneous nature of the data in the smart grid. In this research, we analyzed in detail the security threats of the Generic Object Oriented Substation Events (GOOSE) and Sampled Measured Values (SMV) protocol mappings of the IEC 61850 data modeling standard, which is the most widely industry-accepted standard for power system automation and control. We found that there is a strong need for security solutions that are capable of defending the grid against cyber-attacks, minimizing the damage in case a cyber-incident occurs, and restoring services within minimal time. To address these risks, we focused on correlating cyber security algorithms with physical characteristics of the power system by developing intelligent agents that use this knowledge as an important second line of defense in detecting malicious activity. This will complement the cyber security methods, including encryption and authentication. Firstly, we developed a physical-model-checking algorithm, which uses artificial neural networks to identify switching-related attacks on power systems based on load flow characteristics. Secondly, the feasibility of using neural network forecasters to detect spoofed sampled values was investigated. We showed that although such forecasters have high spoofed-data-detection accuracy, they are prone to the accumulation of forecasting error. In this research, we proposed an algorithm to detect the accumulation of the forecasting error based on lightweight statistical indicators. The effectiveness of the proposed algorithms was experimentally verified on the Smart Grid testbed at FIU. The test results showed that the proposed techniques have a minimal detection latency, in the range of microseconds. Also, in this research we developed a network-in-the-loop co-simulation platform that seamlessly integrates the components of the smart grid together, especially since they are governed by different regulations and owned by different entities. Power system simulation software, microcontrollers, and a real communication infrastructure were combined together to provide a cohesive smart grid platform. A data-centric communication scheme was selected to provide an interoperability layer between multi-vendor devices, software packages, and to bridge different protocols together.