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In the past, there were perceived delineations between the cyber world and the physical world. We are becoming increasingly aware of the overlap between these two worlds, and the overlap itself is increasing. The overlap between these two worlds is known as cyber-physical systems. There have been several incidents involving cyber-physical systems and the number of these incidents is increasing dramatically. In the past there has been no effort to identify methods for describing these incidents in the unique context of cyber-physical systems. This research provides a taxonomy for classifying these incidents that focuses on cross domain, impact oriented analysis. A repository for information about these incidents has also been created as part of this research.

In CPS development and production environments, tightly integrated processes include different engineering disciplines, development and production departments, and software tools working together, where all of the technical engineering processes become strictly intertwined. CPS development and production toolchains have a highly heterogeneous nature, and supporting toolchain architects is necessary for improving the understanding of the interrelationships between tools. To this end, this thesis mainly concentrates on the interoperability of CPS toolchains with an ambition to improve the understanding of interoperability. A literature survey was conducted to analyze the literature on interoperability with an aim to understand how the interoperability is assessed. Findings of the literature review showed that the existing methods mainly use maturity-like assessment models to assess interoperability and they focus on selective aspects of interoperability. These models use distinct levels and do not guide the stakeholders on how to improve the current state of interoperability. This revealed the need for a more flexible approach for assessing interoperability of CPS toolchains. A case study was developed and exercised with an ambition to test the applicability of the visualization approach. In total, three different visualization techniques were evaluated: circular ideogram, node-link diagram, and balloon layout with a clustering algorithm as an extended version of node-link diagram. This thesis concluded by highlighting that data visualizations and visual analytics are not only a method for understanding the interoperability of CPS toolchains, but also a necessity. Data visualization approaches create many opportunities to make interoperability finally visible and the CPS industry should focus its effort on appropriate data collection, usage, and sharing methods in order to best use data visualization and visual analytics technologies. / Cyber-fysiska system (CPS) är ett resultat av mångfacetterade produktutvecklingsprocesser, som innefattar flerdimensionell komplexitet. I CPS:s utvecklings- och produktionsmiljöer, innefattar dessa tätt integrerade processer olika tekniska discipliner, utvecklings- och produktionsavdelningar, och programvaruverktyg som arbetar tillsammans, där alla tekniska ingenjörsprocesser blir strikt sammanflätade. Beslut som fattas av en intressent kan således ha en inverkan på andra intressenter. Verktygskedjor för CPS:s utveckling och produktion har därför en mycket heterogen karaktär, och det är därför nödvändigt med stödjande utvecklare av verktygskedjan för att förbättra förståelsen av sambanden mellan verktyg. För detta ändamål fokuserar denna avhandling främst på interoperabiliteten hos CPS:s verktygskedjor, med ambitionen att förbättra förståelsen för interoperabilitet och, som en följd, vägleda verktygskedjans utvecklare att fatta kostnadseffektiva och hållbara beslut baserade på förbättrad förståelse. En litteraturundersökning genomfördes för att analysera litteratur om interoperabilitet med syfte att förstå hur interoperabilitet bedöms. Resultaten av litteraturgenomgången visade att de befintliga metoderna huvudsakligen använder mognadsliknande bedömningsmodeller för att bedöma interoperabiliteten, och de fokuserar på selektiva aspekter av interoperabiliteten. Dessa modeller använder olika nivåer och vägleder inte intressenterna i hur det aktuella läget för interoperabilitet kan förbättras. Detta visade att det behövs en mer flexibel inställning för att bedöma interoperabiliteten av CPS:s verktygskedjor. Den systematiska litteraturöversikten avslutades genom att tydliggöra att visualisering och visuell analys visar lovande möjligheter för att externalisera den kunskap som nås av bedömningsmodeller med de möjligheter som visualiseringar kan ge. För att studera situationen gällande interoperabilitet i utvecklingen av CPS, utvecklades och genomfördes en fallstudie med ambitionen att testa visualiseringsmetodens tillämplighet. Fallstudien visade en verktygskedjas interoperabilitet, som används för att utveckla ett inbäddat slutet loopkontrollsystem med olika visualiseringstekniker. Totalt har tre olika visualiseringstekniker utvärderas: (a) cirkulärt ideogram, (b) nod- länkdiagram, och (c) ballonglayout med en klusteralgoritm som en utökad version av nodlänkdiagram, vilket gav vissa insikter om vilka tekniker som är mest lämpliga. Varje teknik diskuteras i detalj med ett interoperabilitetsperspektiv. De utmaningar och möjligheter som datavisualisering och visuella analyser ger förklaras dessutom för att synliggöra interoperabilitet. Denna avhandling avslutas med att lyfta fram att datavisualiseringar och visuella analyser inte bara är metoder för att förstå interoperabiliteten av CPS:s verktygskedjor utan också en nödvändighet. Datavisualiseringsmetoder skapar många möjligheter att slutligen göra interoperabilitet synlig och CPS- industrin bör fokusera sina ansträngningar på lämplig datainsamling, användande och delningsmetoder för att på bästa sätt utnyttja datavisualisering och visuella analystekniker. / <p>QC 20170203</p>

The aim of this paper was to investigate whether infrastructure could be modelled in order to find critical points using network science and graph theory. Since a lot of information about ourinfrastructures is publicly available, an attacker might exploit this to find vulnerabilities in our systems. With that in mind, the methods of this paper were implemented from an attackers point of view who’d want to maximize harm with minimal effort. The Swedish railway network served as an example and starting point for the optimization of the methods. The data for the network was obtained from the Swedish Transport Agency’s website and was implemented in Networkx using Python. Different centrality metrics were used to identify and remove critical nodes in the network. The centrality metrics were also used to rank the nodes and to remove them after order of importance as the size of the largest component was recorded. This was done both with no recalculation and with a recalculation after each removal. The results were compared with the random removal of nodes, and it showed that without a recalculation the random removal performed better but with recalculation all the centrality metrics performed significantly better. The Swedish railway network is a sensitive network in terms of how it is connected. Targeting a few nodes could completely cut off parts of the graph, creating two sub components with no way of traveling between them. Many different methods can identify these nodes, but only a few are suitable in terms of generic results that could work on other networks as well. The most prominent one being the one dealing with degree and connectivity. The nodes that had a higher degree than connectivity between themselves and the source, identified nodes that would completely disrupt the network, leaving two subcomponents. Infrastructures can be seen as highly intertwined systems, where the physical-, cyber- and human parts all affect and interact with each other.

Power systems constitute a pillar of the critical infrastructure and, as a result, their cybersecurity is paramount. Traditional power system architectures are moving from their original centralized nature to a distributed paradigm. This transition has been propelled by the rapid penetration of distributed energy resources (DERs) such as rooftop solar panels, battery storage, etc. However, with the introduction of new DER devices, technologies, and operation models, the threat surface of power systems is inadvertently expanding. This dissertation provides a comprehensive overview of the cybersecurity landscape of DER-enabled power systems outlining potential attack entry points, system vulnerabilities, and the corresponding cyberattack impacts. Cyber-physical energy systems (CPES) testbeds are crucial tools to study power systems and perform vulnerability analyses, test security defenses, and evaluate the impact of cyberattacks in a controlled manner without impacting the actual electric grid. This work also attempts to provide bottom-up security solutions to secure power systems from their lowest abstraction layer, i.e., hardware. Specifically, custom-built hardware performance counters (HPCs) are proposed for the detection of malicious firmware, e.g., malware, within DER inverter controllers. The experimental results prove that HPCs are an effective host-based defense and can accurately identify malicious firmware with minimum performance overheads. Also, methodologies to secure communication protocols and ensure the nominal operation of DER devices using physics-informed schemes are presented. First, DERauth, a battery-based secure authentication primitive that can be used to enhance the security of DER communication, is proposed and evaluated in a CPES testbed. Then, a physics-based attack detection scheme that leverages system measurements to construct models of autonomous DER agents is presented. These measurement-based models are then used to discern between nominal and malicious DER behavior. The dissertation concludes by discussing how the proposed defense mechanisms can be used synergistically in an automated framework for grid islanding to improve power system security and resilience, before it provides prospective directions for future research.

Die Modellfabrik der FH Münster erlaubt durch den Umfang und die Komplexität der enthaltenen Automatisierungsaufgaben sowie einen Aufbau aus industriellen Komponenten eine praxisnahe Lehre im Bereich aktueller Anlagenautomatisierung und darüber hinausgehenden Funktionen im Sinne einer durchgängigen Digitalisierung. Die verwendete Unterscheidung der durchgängigen Digitalisierung in horizontale und vertikale Verknüpfungen wird veranschaulicht. Aufbauend auf Erfahrungen mit der Vorgängeranlage werden Neuerungen der 2021 aufgebauten neuen Modellfabrik vorgestellt. Neuerungen umfassen insbesondere die Modularisierung der Anlage, das umgesetzte Sicherheitskonzept, einen Webshop mit Onlinekonfigurator, eine Webvisualiserung des Anlagenzustandes inklusive der Energieverbräuche, sowie Möglichkeiten zur virtuellen Inbetriebnahme. Weiterhin wird das aktuelle Konzept zur Erweiterung der horizontalen digitalen Durchgängigkeit mittels der Einbindung eines autonomen mobilen Roboters in die Modellfabrik vorgestellt.

Die Modellfabrik der FH Münster erlaubt durch den Umfang und die Komplexität der enthaltenen Automatisierungsaufgaben sowie einen Aufbau aus industriellen Komponenten eine praxisnahe Lehre im Bereich aktueller Anlagenautomatisierung und darüber hinausgehenden Funktionen im Sinne einer durchgängigen Digitalisierung. Die verwendete Unterscheidung der durchgängigen Digitalisierung in horizontale und vertikale Verknüpfungen wird veranschaulicht. Aufbauend auf Erfahrungen mit der Vorgängeranlage werden Neuerungen der 2021 aufgebauten neuen Modellfabrik vorgestellt. Neuerungen umfassen insbesondere die Modularisierung der Anlage, das umgesetzte Sicherheitskonzept, einen Webshop mit Onlinekonfigurator, eine Webvisualiserung des Anlagenzustandes inklusive der Energieverbräuche, sowie Möglichkeiten zur virtuellen Inbetriebnahme. Weiterhin wird das aktuelle Konzept zur Erweiterung der horizontalen digitalen Durchgängigkeit mittels der Einbindung eines autonomen mobilen Roboters in die Modellfabrik vorgestellt.

Risk assessment is a critical aspect of all businesses, and leaders are tasked with limiting risk to the lowest reasonable level within their systems. Industrial Control Systems (ICS) operate in a different cybersecurity risk environment than business systems due to the possibility of second and third-order effects when an attack occurs. We present a process for predicting when an adversary gains the ability to attack an industrial control system. We assist leaders in understanding how attackers are targeting ICS by providing visualizations and percentages that can be applied to updating infrastructure or shifting personnel responsibilities to counter the threat. This new process seeks to integrate defenders and threat intelligence providers, allowing defenders to proactively defend their networks prior to devastating attacks. We apply the process by observing it under randomness with constraints and through a case study of the 2015 attack on the Ukrainian power grid. We find that this process answers the question of what an attacker can do, provides the ability for the defender to possess an updated understanding of the threat’s capability, and can both increase and decrease the probability that an attacker has a capability against a control system. This process will allow leaders to provide strategic vision to the businesses and systems that they manage.

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