Purpose: Operational technology (OT) environments face significant risks and threats stemming from Industry 4.0. The security landscape for OT is confronted with unprecedented challenges due to the expanding attack surface resulting from factors like cloud adoption, Industrial Internet of Things, and increased mobility. Securing OT networks has become increasingly complex, and relying solely on perimeter firewalls or air gaps is a flawed approach. Malicious actors now target OT systems for high-stakes ransoms and lockouts, exploiting the manufacturing industry's reluctance to disrupt operations. Conventional security measures are insufficient against insider threats and agile hackers who can maneuver within the network. These adversaries display patience and persistence, often waiting for months to gain unauthorized access.  Acknowledging the complexity of OT within industrial organizations, the objective of this master's thesis is to offer a set of simplified principles and practices that can serve as valuable guidance for practitioners seeking to establish effective Attack Surface Management (ASM) strategies in OT environments. These OT security practices embody a comprehensive approach to cybersecurity, empowering OT security practitioners to adapt to ever-evolving industry dynamics and establish baseline protection against various threats and vulnerabilities. Design/Methodology/Approach: This thesis utilizes Action Design Research (ADR), which combines Action Research (AR) and Design Science (DS) approaches. ADR is applied to address a specific problem in an organizational context, involving intervention, evaluation, and the creation of new IT principles and practices. ADR is chosen as the appropriate methodology to guide the development and evaluation of a prototype OT Remote Connectivity and the secure integration of MES components into the organizational OT environment. Findings: This study made a valuable contribution to the field by introducing five innovative Design Principles (DPs) specifically designed to simplify ASM in OT environments. These newly proposed DPs complement the existing ones and address emerging challenges and considerations in the rapidly evolving landscape of OT security. They provide practitioners with fresh perspectives, guidelines, and approaches to enhance the effectiveness and efficiency of ASM strategies in OT. Practical Implications: The research project gives a comprehensive checklist of secure practices for OT, these were formulated and implemented, considering the entire lifecycle of OT devices. These practices encompassed various stages, from design, procurement to disposal, and aimed to enhance the security posture of OT systems. Building upon these secure practices, a functional prototype was developed to facilitate secure remote connectivity for suppliers/vendors and the seamless integration of Manufacturing Execution System (MES) components.

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<p>Cyber-Physical Systems (CPS) are integrated systems that consist of the computational and physical components with network communication to support operation in the physical world. My PhD dissertation focuses on the security and reliability of autonomous cyber-physical systems, such as self-driving cars, drones, and underwater robots, that are safety-critical systems based on the seamless integration of cyber and physical components. Autonomous CPS are becoming an integral part of our life. The market for autonomous driving systems is expected to be more than $65 billion by 2026. The security of such CPS is hence critical. Beyond traditional cyber-only computing systems, these complex and integrated CPS have unique characteristics. From the security perspective, they open unique research opportunities since they introduce additional attack vectors and post new challenges that existing cyber-oriented approaches cannot address well. <em>The goal of my research is to build secure and reliable autonomous CPS by bridging the gap between the cyber and physical domains.</em> To this end, my work focuses on fundamental research questions associated with cyber-physical attack and defense, vulnerability discovery and elimination, and post-attack investigation. My approach to solving the problems involves various techniques and interdis- ciplinary knowledge, including program analysis, search-based software engineering, control theory, robotics, and AI/machine learning.</p>

Several calamities occur throughout the world each year, resulting in varying losses. Disasters wreak havoc on infrastructures and impair operation. They result in human deaths and injuries and stress people's mental and emotional states. These negative impacts of natural disasters induce significant economic losses, as demonstrated by the $ 423 billion loss in 2011 in Tohoku, Japan, and the $ 133 billion loss in hurricane Harvey, U.S.A. Every year, hurricanes and tropical storms result in 10,000 human deaths worldwide. To mitigate losses, communities' readiness, flexibility, and resilience must be strengthened. To this end, appropriate techniques for forecasting a community's capacity and functionality in the face of impending crises must be developed and suitable community resilience metrics and their quantification must be established. Collaboration between critical infrastructures such as power systems and emergency services and social networks is critical for building a resilient community. As a result, we require metrics that account for both the social and infrastructure aspects of the community. While the literature on critical infrastructures such as power systems discusses the effect of social factors on resilience, they do not model these social factors and metrics due to their complexity. On the other hand, it turns out that the role of critical infrastructures and some critical social characteristics is overlooked in the computational social science literature on community resilience. Thus, this dissertation presents a multi-agent socio-technical model of community resilience, taking into account the interconnection of power systems, emergency services, and social communities. We offer relevant measures for each section and describe dynamic change and its dependence on other metrics using a variety of theories and expertise from social science, psychology, electrical engineering, and emergency services. To validate the model, we used data on two hurricanes (Irma and Harvey) collected from Twitter, GoogleTrends, FEMA, power utilities, CNN, and Snopes (a fact-checking organization). We also describe methods for quantifying social metrics such as anxiety, risk perception, cooperation using social sensing, natural language processing, and text mining tools. / Doctor of Philosophy / Power systems serve social communities that consist of residential, commercial, and industrial customers. The social behavior and degree of collaboration of all stakeholders, such as consumers, prosumers, and utilities, affect the level of preparedness, mitigation, recovery, adaptability, and, thus, power system resilience. Nonetheless, the literature pays scant attention to stakeholders' social characteristics and collaborative efforts when confronted with a disaster and views the problem solely as a cyber-physical system. However, power system resilience, which is not a standalone discipline, is inherently a cyber-physical-social problem, making it complex to address. To this end, in this dissertation, we develop a socio-technical power system resilience model based on neuroscience, social science, and psychological theories and use the threshold model to simulate the behavior of power system stakeholders during a disaster. We validate our model using datasets of hurricane Harvey of Category 4 that hit Texas in August 2017 and hurricane Irma of Category 5 that made landfall in Florida in September 2017. We retrieve these datasets from Twitter and GoogleTrend and then apply natural language processing and language psychology analysis tools to deduce the social behavior of the end-users.

Indoor localization remains an open problem in geolocation research, and once this is solved the localization enables counting and tracking of building occupants. This information is vital in an emergency, enables occupancy-optimized heating or cooling, and assists smart buildings in tailoring services for occupants. Unfortunately, two prevalent technologies---GPS and cellular-based positioning---perform poorly indoors due to attenuation and multipath from the building. To address this issue, the research community devised many alternatives for indoor localization (e.g., beacons, RFID tags, Wi-Fi fingerprinting, and UWB to cite just a few examples). A drawback with most is the requirement for those being located to carry a properly-configured device at all times. An alternative based on computer vision techniques poses significant privacy concerns due to cameras recording building occupants. By contrast, ILoViT research makes novel use of accelerometers already present in some buildings. These sensors were originally intended to monitor structural health or to study structural dynamics. The key idea is that when a person's footstep-generated floor vibrations can be detected and located then it becomes possible to locate persons moving within a building. Vibration propagation in buildings has complexities not encountered by acoustic or radio wave propagation in air; thus, conventional localization algorithms are inadequate. ILoVIT algorithms account for these conditions and have been demonstrated in a public building to provide sub-meter accuracy. Localization provides the foundation for counting and tracking, but providing these additional capabilities confronts new challenges. In particular, how does one determine the correct association of footsteps to the person making them? The ILoViT research created two methods for solving the data association problem. One method only provides occupancy counting but has modest, polynomial time complexity. The other method draws inspiration from prior work in the radar community on the multi-target tracking problem, specifically drawing from the multiple hypothesis tracking strategy. This dissertation research makes new enhancements to this tracking strategy to account for human gait and characteristics of footstep-derived multilateration. The Virginia Polytechnic Institute and State University's College of Engineering recognized this dissertation research with the Paul E. Torgersen Graduate Student Research Excellence Award. / Ph. D.

The power grid has changed a great deal from what has been generally viewed as a traditional power grid. The modernization of the power grid has seen an increase in the integration and incorporation of computing and communication elements, creating an interdependence of both physical and cyber assets of the power grid. The fast-increasing connectivity has transformed the grid from what used to be primarily a physical system into a Cyber- Physical System (CPS). The physical elements within a power grid are well understood by power engineers; however, the newly deployed cyber aspects are new to most researchers and operators in this field. The new computing and communications structure brings new vulnerabilities along with all the benefits it provides. Cyber security of the power grid is critical due to the potential impact it can make on the community or society that relies on the critical infrastructure. These vulnerabilities have already been exploited in the attack on the Ukrainian power grid, a highly sophisticated, multi-layered attack which caused large power outages for numerous customers. There is an urgent need to understand the cyber aspects of the modernized power grid and take the necessary precautions such that the security of the CPS can be better achieved. The power grid is dependent on two main cyber infrastructures, i.e., Supervisory Control And Data Acquisition (SCADA) and Advanced Metering Infrastructure (AMI). This thesis investigates the AMI in power grids by developing a testbed environment that can be created and used to better understand and develop security strategies to remove the vulnerabilities that exist within it. The testbed is to be used to conduct and implement security strategies, i.e., an Intrusion Detections Systems (IDS), creating an emulated environment to best resemble the environment of the AMI system. A DoS flooding attack and an IDS are implemented on the emulated testbed to show the effectiveness and validate the performance of the emulated testbed. / M.S. / The power grid is becoming more digitized and is utilizing information and communication technologies more, hence the smart grid. New systems are developed and utilized in the modernized power grid that directly relies on new communication networks. The power grid is becoming more efficient and more effective due to these developments, however, there are some considerations to be made as for the security of the power grid. An important expectation of the power grid is the reliability of power delivery to its customers. New information and communication technology integration brings rise to new cyber vulnerabilities that can inhibit the functionality of the power grid. A coordinated cyber-attack was conducted against the Ukrainian power grid in 2015 that targeted the cyber vulnerabilities of the system. The attackers made sure that the grid operators were unable to observe their system being attacked via Denial of Service attacks. Smart meters are the digitized equivalent of a traditional energy meter, it wirelessly communicates with the grid operators. An increase in deployment of these smart meters makes it such that we are more dependent on them and hence creating a new vulnerability for an attack. The smart meter integration into the power grid needs to be studied and carefully considered for the prevention of attacks. A testbed is created using devices that emulate the smart meters and a network is established between the devices. The network was attacked with a Denial of Service attack to validate the testbed performance, and an Intrusion detection method was developed and applied onto the testbed to prove that the testbed created can be used to study and develop methods to cover the vulnerabilities present.

<p dir="ltr">Deep-space extraterrestrial missions require operating, supporting, and maintaining complex habitat systems at light minutes from Earth.</p><p dir="ltr">These habitation systems operate in harsh, unforgiving environments, will be sparsely crewed, and must be more autonomous than current space habitats, as communication delays will severely constrain Earth-based support.</p><p dir="ltr">Long-duration missions, limited knowledge of the extraterrestrial environment, and the need for self-sufficiency make these habitats vulnerable to a wide range of risks and failures, many of which are impossible to premeditate.</p><p dir="ltr">Therefore, it is necessary to design these systems to be resilient to faults and failures, thoughtfully designed to be situationally aware of their operational state and engage control mechanisms that maintain safe operations when migrating towards unsafe regions of operation.</p><p dir="ltr">Resilience-oriented design of such systems requires a holistic systems approach that represents the system's dynamic behavior, its control-oriented behaviors, and the interactions between them as it navigates through regions of safe and unsafe operations.</p><p dir="ltr">Only through this integrated approach can we fully understand how the system will behave under various conditions and design controls to prevent performance loss and ensure resilient operations.</p><p dir="ltr">Systems health management (SHM) is a key component for the resilience-oriented design of extraterrestrial habitats.</p><p dir="ltr">SHM capabilities enable intelligent autonomous control capabilities that can:</p><p dir="ltr">a) sense, diagnose, and isolate the root causes of anomalies,</p><p dir="ltr">b) predict how the system's behavior may evolve, and</p><p dir="ltr">c) select and execute recovery actions to restore system performance when appropriate.</p><p dir="ltr">Modern SHM technologies increasingly rely on intelligent autonomous control capabilities to manage system health and adapt behavior to maintain system performance.</p><p dir="ltr">This is achieved through complex nonlinear informational dependencies and control feedback loops that are difficult to design and verify using traditional risk assessment and resilience engineering methods.</p><p dir="ltr">This research contributes to enhancing the conceptual and preliminary design phases for developing resilient complex systems with embedded intelligent control-oriented behaviors.</p><p dir="ltr">It presents the required systems engineering tools and frameworks, enabling us to study the dynamic behavior of systems as they approach and recover from unsafe operations.</p><p dir="ltr">Further, it demonstrates how these tools and frameworks can quantify and gain insights into system resilience and support engineering decisions.</p><p dir="ltr">The work is contextualized within the broader systems engineering approach for designing complex, resilient extraterrestrial habitation systems.</p>

<p dir="ltr">In the context of a Human-in-the-Loop (HITL) system, the accuracy of reachability analysis plays a significant role in ensuring the safety and reliability of HITL systems. In addition, one can avoid unnecessary conservativeness by explicitly considering human control behavior compared to those methods that rely on the system dynamics alone. One possible approach is to use a Gaussian Mixture Model (GMM) to encode human control behavior using the Expectation-Maximization (EM) algorithm. However, relatively few works consider the admissible control input ranges due to physical limitations when modeling human control behavior. This could make the following reachability analysis overestimate the system's capability, thereby affecting the performance of the HITL system. To address this issue, this work presents a constrained stochastic reachability analysis algorithm that can explicitly account for the admissible control input ranges. By confining the ellipsoidal confidence region of each Gaussian component using Sequential Quadratic Programming (SQP), we probabilistically constrain the GMM as well as the corresponding stochastic reachable sets. A comprehensive mathematical analysis of how the constrained GMM can affect the stochastic reachable sets is provided in this work. Finally, the proposed stochastic reachability analysis algorithm is validated via an illustrative numerical example.</p>

La thèse présente le développement de CPS (CMOS Pixel Sensors) intégré avec CAN au niveau du pixel pour les couches externes du détecteur de vertex de l’ILD (International Large Detector). Motivé par la physique dans l’ILC (International Linear Collider), une précision élevée est nécessaire pour les détecteurs. La priorité des capteurs qui montre sur les couches externes est une faible consommation d’énergie en raison du rapport élevé de couverture de la surface sensible (~90%) dans le détecteur de vertex. Le CPS intégré avec CAN est un choix approprié pour cette application. L’architecture de CAN de niveau colonne ne fournit pas une performance optimisée en termes de bruit et la consommation d’énergie. La conception de CAN au niveau du pixel a été proposée. Bénéficiant des sorties de pixels tout-numérique, CAN au niveau des pixels présentent les mérites évidents sur le bruit, la vitesse, la zone sensible et la consommation d’énergie. Un prototype de capteur, appelé MIMADC, a été implémenté par un processus de 0.18 μm CIS (CMOS Image Sensor). L’objectif de ce capteur est de vérifier la faisabilité du CPS intégré avec les CAN au niveau des pixels. Trois matrices sont incluses dans ce prototype, mais avec deux types différents de CAN au niveau de pixel: une avec des CAN à registre à approximations successives (SAR), et les deux autres avec des CAN à une seule pente (Single-Slope, SS) CAN. Toutes les trois possédant les pixels de la même taille de 35×35 μm2 et une résolution de 3-bit. Dans ce texte, des analyses théoriques et le prototype sont présentés, ainsi que la conception détaille des circuits. / This thesis presents the development of CMOS pixel sensors (CPS) integrated with pixel-level ADCs for the outer layers of the ILD (International Large Detector) vertex detector. Driven by physics in the ILC (International Linear Collider), an unprecedented precision is required for the detectors. The priority of the sensors mounted on the outer layers is low power consumption due to the large coverage ratio of the sensitive area (~90%) in the vertex detector. The CPS integrated with ADCs is a promising candidate for this application. The architecture of column-level ADCs, exists but do not provide an optimized performance in terms of noise and power consumption. The concept of pixel-level ADCs has been proposed. Benefiting from the all-digital pixel outputs, pixel-level ADCs exhibit the obvious merits on noise, speed, insensitive area, and power consumption. In this thesis, a prototype sensor, called MIMADC, has been implemented by a 0.18 μm CIS (CMOS Image Sensor) process. The target of this sensor is to verify the feasibility of the CPS integrated with pixel-level ADCs. Three matrices are included in this prototype but with two different types of pixel-level ADCs: one with successive approximation register (SAR) ADCs, and the other two with single-slope (SS) ADCs. All of them feature a same pixel size of 35×35 μm2 and a resolution of 3-bit. In this thesis, the prototype is presented for both theoretical analyses and circuit designs. The test results of the prototype are also presented.

Ce travail se place dans le contexte du détecteur de vertex (VXD) composé de capteurs CMOS pour l'ILC, et dans celui du télescope en faisceau du projet européen AIDA. La thèse inclut les tests en faisceau des éléments du télescope AIDA : les super-plans SALAT et les échelles double faces PLUME. Elle questionne la valeur ajoutée en terme d'alignement, des couches double faces de capteurs CMOS pour le VXD de l'ILD. Une nouvelle méthode d'alignement autonome de chacune des 3 double couches du VXD grâce aux mini-vecteurs construits sur chaque zone de recouvrement inter-échelle est proposée et a été testée avec des particules de haute impulsion. Cependant, seules les particules du bruit de fond faisceau, de plus basses impulsions, permettent l'obtention d'une statistique suffisante pour cet alignement. Ce bruit de fond a alors été étudié et une estimation des taux d'occupation des capteurs du VXD a conduit à une ré-estimation des vitesses de lecture des capteurs de chaque couche du VXD. / This work was conducted in the context of a vertex detector (VXD) composed of CMOS sensors for ILD and in the context of the beam telescope of the european project AIDA. The provides the results of beam tests for the new telescope components : the SALAT super-planes and the PLUME double sided ladders. The thesis adresses the added value in terms of alignment, of double sided layers of CMOS sensors for the VXD of ILD. A new standalone alignment method of each of the three double sided layers of VXD with the mini-vectors built on each overlapping zone between the consecutive ladders is analysed. Such alignment was validated with high momentum particles. However, only the beam background particles, with lower momentum, can provide the minimum statistic for this kind of alignment. Thus, the beam background noise was studied and the occupancy rate of the VXD sensors was studied. This led to a reassessment of the readout speed for the sensors of each layer of the VXD.