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Modern society is more than ever striving for digital connectivity -- everywhere and at any time, giving rise to megatrends such as the Internet of Things (IoT). Already today, 'things' communicate and interact autonomously with each other and are managed in networks. In the future, people, data, and things will be interlinked, which is also referred to as the Internet of Everything (IoE). Billions of devices will be ubiquitously present in our everyday environment and are being connected over the Internet.
As an emerging technology, printed electronics (PE) is a key enabler for the IoE offering novel device types with free form factors, new materials, and a wide range of substrates that can be flexible, transparent, as well as biodegradable. Furthermore, PE enables new degrees of freedom in circuit customizability, cost-efficiency as well as large-area fabrication at the point of use.
These unique features of PE complement conventional silicon-based technologies. Additive manufacturing processes enable the realization of many envisioned applications such as smart objects, flexible displays, wearables in health care, green electronics, to name but a few.
From the perspective of the IoE, interconnecting billions of heterogeneous devices and systems is one of the major challenges to be solved. Complex high-performance devices interact with highly specialized lightweight electronic devices, such as e.g. smartphones and smart sensors. Data is often measured, stored, and shared continuously with neighboring devices or in the cloud. Thereby, the abundance of data being collected and processed raises privacy and security concerns.
Conventional cryptographic operations are typically based on deterministic algorithms requiring high circuit and system complexity, which makes them unsuitable for lightweight devices.
Many applications do exist, where strong cryptographic operations are not required, such as e.g. in device identification and authentication. Thereby, the security level mainly depends on the quality of the entropy source and the trustworthiness of the derived keys. Statistical properties such as the uniqueness of the keys are of great importance to precisely distinguish between single entities.
In the past decades, hardware-intrinsic security, particularly physically unclonable functions (PUFs), gained a lot of attraction to provide security features for IoT devices. PUFs use their inherent variations to derive device-specific unique identifiers, comparable to fingerprints in biometry.
The potentials of this technology include the use of a true source of randomness, on demand key derivation, as well as inherent key storage.
Combining these potentials with the unique features of PE technology opens up new opportunities to bring security to lightweight electronic devices and systems. Although PE is still far from being matured and from being as reliable as silicon technology, in this thesis we show that PE-based PUFs are promising candidates to provide key derivation suitable for device identification in the IoE.
Thereby, this thesis is primarily concerned with the development, investigation, and assessment of PE-based PUFs to provide security functionalities to resource constrained printed devices and systems.
As a first contribution of this thesis, we introduce the scalable PE-based Differential Circuit PUF (DiffC-PUF) design to provide secure keys to be used in security applications for resource constrained printed devices. The DiffC-PUF is designed as a hybrid system architecture incorporating silicon-based and inkjet-printed components. We develop an embedded PUF platform to enable large-scale characterization of silicon and printed PUF cores.
In the second contribution of this thesis, we fabricate silicon PUF cores based on discrete components and perform statistical tests under realistic operating conditions. A comprehensive experimental analysis on the PUF security metrics is carried out. The results show that the silicon-based DiffC-PUF exhibits nearly ideal values for the uniqueness and reliability metrics. Furthermore, the identification capabilities of the DiffC-PUF are investigated and it is shown that additional post-processing can further improve the quality of the identification system.
In the third contribution of this thesis, we firstly introduce an evaluation workflow to simulate PE-based DiffC-PUFs, also called hybrid PUFs. Hereof, we introduce a Python-based simulation environment to investigate the characteristics and variations of printed PUF cores based on Monte Carlo (MC) simulations. The simulation results show, that the security metrics to be expected from the fabricated devices are close to ideal at the best operating point.
Secondly, we employ fabricated printed PUF cores for statistical tests under varying operating conditions including variations in ambient temperature, relative humidity, and supply voltage. The evaluations of the uniqueness, bit aliasing, and uniformity metrics are in good agreement with the simulation results. The experimentally determined mean reliability value is relatively low, which can be explained by the missing passivation and encapsulation of the printed transistors. The investigation of the identification capabilities based on the raw PUF responses shows that the pure hybrid PUF is not suitable for cryptographic applications, but qualifies for device identification tasks.
The final contribution is to switch to the perspective of an attacker. To judge on the security capabilities of the hybrid PUF, a comprehensive security analysis in the manner of a cryptanalysis is performed. The analysis of the entropy of the hybrid PUF shows that its vulnerability against model-based attacks mainly depends on the selected challenge building method. Furthermore, an attack methodology is introduced to assess the performances of different mathematical cloning attacks on the basis of eavesdropped challenge-response pairs (CRPs). To clone the hybrid PUF, a sorting algorithm is introduced and compared with commonly used supervised machine learning (ML) classifiers including logistic regression (LR), random forest (RF), as well as multi-layer perceptron (MLP).
The results show that the hybrid PUF is vulnerable against model-based attacks. The sorting algorithm benefits from shorter training times compared to the ML algorithms. If the eavesdropped CRPs are erroneous, the ML algorithms outperform the sorting algorithm.
With this generation of devices, Virtual Reality (VR) has actually made it into the living rooms of end-users. These devices feature 6-DOF tracking, allowing them to move naturally in virtual worlds and experience them even more immersively. However, for a natural locomotion in the virtual, one needs a corresponding free space in the real environment. The available space is often limited, especially in everyday environments and under normal spatial conditions. Furnishings and objects of daily life can quickly become obstacles for VR users if they are not cleared away. Since the idea behind VR is to place users into a virtual world and to hide the real world as much as possible, invisible objects represent potential obstacles. The currently available systems offer only rudimentary assistance for this problem. If a user threatens to leave the space previously defined for use, a visual boundary is displayed to allow orientation within the space. These visual metaphors are intended to prevent users from leaving the safe area. However, there is no detection of potentially dangerous objects within this part of space. Objects that have not been cleared away or that have been added in the meantime may still become obstacles. This thesis shows how possible obstacles in the environment can be detected automatically with range imaging cameras and how users can be effectively warned about them in the virtual environment without significantly disturbing their sense of presence. Four different interactive visual metaphors are used to signalize the obstacles within the VE. With the help of a user study, the four signaling variants and the obstacle detection were evaluated and tested.
In the work at hand, we state that privacy and malleability of data are two aspects highly desired but not easy to associate. On the one hand, we are trying to shape data to make them usable and editable in an intelligible way, namely without losing their initial information. On the other hand, we are looking for effective privacy on data such that no external or non-authorized party could learn about their content. In such a way, we get overlapping requirements by pursuing different goals; it is trivial to be malleable without being secure, and vice versa. We propose four “real-world” use cases identified as scenarios where these two contradictory features are required and taking place in distinct environments. These considered backgrounds consist of firstly, cloud security auditing, then privacy of mobile network users and industry 4.0 and finally, privacy of COVID-19 tracing app users. After presenting useful background material, we propose to employ multiple approaches to design solutions to solve the use cases. We combine homomorphic encryption with searchable encryption and private information retrieval protocol to build an effective construction for the could auditing use case. As a second step, we develop an algorithm to generate the appropriate parameters to use the somewhat homomorphic encryption scheme by considering correctness, performance and security of the respective application. Finally, we propose an alternative use of Bloom filter data structure by adding an HMAC function to allow an outsourced third party to perform set relations in a private manner. By analyzing the overlapping bits occurring on Bloom filters while testing the inclusiveness or disjointness of the sets, we show how these functions maintain privacy and allow operations directly computed on the data structure. Then, we show how these constructions could be applied to the four selected use cases. Our obtained solutions have been implemented and we provide promising results that validate their efficiency and thus relevancy.
Das Ziel der Arbeit ist es, die Wirkung von datenschutzbezogenen Gütesiegeln auf das Vertrauen, die Teilnahmebereitschaft und die freiwillige Datenbekanntgabe in Webbefragungen zu untersuchen. Hierbei soll der unternehmerische Nutzen im Kontext der deutschen Markt-, Medien- und Sozialforschung transparent gemacht werden. Da sich an diesem Markt überwiegend kleine und mittlere Forschungseinrichtungen befinden, werden die wirtschaftlichen Belange dieser Unternehmen besonders berücksichtigt. Insgesamt beschäftigt sich die Arbeit durch den besonderen Branchenbezug zur deutschen Markt-, Medien- und Sozialforschung mit einem neuartigen Forschungsfeld. Vor diesem Hintergrund werden die konzeptionellen und theoretischen Grundlagen, die zum Einsatz von Gütesiegeln im E-Commerce vorliegen, in einem neuen Licht betrachtet. Dabei liegt die Besonderheit der Arbeit darin, dass sie sich mit der freiwilligen Bekanntgabe von persönlichen Daten auf der Basis von intrinsisch motivierten Faktoren befasst.
The last decades have seen the evolution of industrial production into more sophisticated processes. The development of specialized, high-end machines has increased the importance of predictive maintenance of mechanical systems to produce high-quality goods and avoid machine breakdowns. Predictive maintenance has two main objectives: to classify the current status of a machine component and to predict the maintenance interval by estimating its remaining useful life (RUL). Nowadays, both objectives are covered by machine learning and deep learning approaches and require large training datasets that are often not available. One possible solution may be transfer learning, where the knowledge of a larger dataset is transferred to a smaller one. This thesis is primarily concerned with transfer learning for predictive maintenance for fault classification and RUL estimation. The first part presents the state-of-the-art machine learning techniques with a focus on techniques applicable to predictive maintenance tasks (Chapter 2). This is followed by a presentation of the machine tool background and current research that applies the previously explained machine learning techniques to predictive maintenance tasks (Chapter 3). One novelty of this thesis is that it introduces a new intermediate domain that represents data by focusing on the relevant information to allow the data to be used on different domains without losing relevant information (Chapter 4). The proposed solution is optimized for rotating elements. Therefore, the presented intermediate domain creates different layers by focusing on the fault frequencies of the rotating elements. Another novelty of this thesis is its semi and unsupervised transfer learning-based fault classification approach for different component types under different process conditions (Chapter 5). It is based on the intermediate domain utilized by a convolutional neural network (CNN). In addition, a novel unsupervised transfer learning loss function is presented based on the maximum mean discrepancy (MMD), one of the state-of-the-art algorithms. It extends the MMD by considering the intermediate domain layers; therefore, it is called layered maximum mean discrepancy (LMMD). Another novelty is an RUL estimation transfer learning approach for different component types based on the data of accelerometers with low sampling rates (Chapter 6). It applies the feature extraction concepts of the classification approach: the presented intermediate domain and the convolutional layers. The features are then used as input for a long short-term memory (LSTM) network. The transfer learning is based on fixed feature extraction, where the trained convolutional layers are taken over. Only the LSTM network has to be trained again. The intermediate domain supports this transfer learning type, as it should be similar for different component types. In addition, it enables the practical usage of accelerometers with low sampling rates during transfer learning, which is an absolute novelty. All presented novelties are validated in detailed case studies using the example of bearings (Chapter 7). In doing so, their superiority over state-of-the-art approaches is demonstrated.
Printed electronics, due to its manufacturability using printing technology, allows for fabrication on large areas and the usage of flexible substrates and thus enables novel applications. Non-impact printing technology, such as inkjet-printing, permits for flexible, decentralized manufacturing of electronic devices and systems. This further facilitates split-manufacturing in security-critical electrical components, as well as a maximum in design flexibility in terms of free form factors and non-standardized structures with different geometrical sizes, reaching from a few micrometers up to several millimeters.
Based on the technological benefits printed electronics offers, it provides an interesting counterpart to classical silicon-based electronics, which is usually densely integrated on miniaturized, rigid areas. By utilizing both technologies in a complementary manner, novel systems in the form of hybrid systems can be enabled. Whilst hybrid systems, incorporating passive printed components and electrically conductive wiring concepts, are already commercialized, complex printed systems, which also utilize active components remain rare. To enable more complex (hybrid) systems, various building blocks are required. This includes possibilities for lightweight, printed data storage, the capability to provide sustainable, self-powered printed components and especially circuits for secure, unique identification for holistic printed systems, deployed in the internet of things.
The presented thesis focuses on inkjet-printed electronic devices, circuits and hybrid systems. It investigates solutions for current scientific questions in the area of efficient data storage, sustainable electronics and hardware-based security in printed electronics.
For data storage, an inkjet-printed memristor is developed. The device is fully electrically evaluated with a focus on its data storage capabilities. Furthermore, the printed device is of special interest due to its easy manufacturability and integration capabilities. The experimental analysis reveals that the developed memristor is highly suitable as lightweight non-volatile memory device.
In order to enable sustainable electronic systems, an inkjet-printed full-wave rectifier based on near-zero threshold voltage electrolyte-gated transistors is developed and fully electrically characterized. The circuit is capable for small alternating voltage rectification of low-frequency vibration energy harvesters in the sub-volt region. This provides an important building block in enabling sustainable, self-powered electronic systems. The inkjet-printed full-wave rectifier is evaluated by electrical simulation and experimentally.
To tackle hardware-based security for printed electronics, two implementations for inkjet-printed physically unclonable functions are developed and presented. For unique identification, intrinsic variation in active printed devices are exploited. One implementation is based on a crossbar architecture, incorporating integrable electrolyte-gated transistor cells. The second implementation, the so-called differential circuit physically unclonable function, is based on inverter structures, which provide the basis for unique response generation. Both physically unclonable functions are evaluated using an electrical simulation-based approach and experimentally. The differential circuit approach is furthermore fully integrated within a silicon-based electronic platform environment and serves as intrinsic variation source in a hybrid system. The hybrid system physically unclonable function is fully verified regarding performance metrics and is capable to generate highly unique responses for secure identification.
Entwicklung und Evaluierung eines adaptiv-prädiktiven Algorithmus für thermoaktive Bauteilsysteme
(2017)
Der Gebäudesektor ist einer der Hauptverbraucher von Energie und somit mitverantwortlich für einen wesentlichen Anteil an CO2-Emissionen. Heiz- und Kühlkonzepte, die erneuerbare Energiequellen nutzen können, gewinnen daher immer mehr an Bedeutung. Hierfür besonders geeignet sind Niedertemperatursysteme, wie beispielsweise Thermoaktive Bauteilsysteme (TABS). Die große thermische Trägheit und die geringe Leistung dieser Systeme verhindern eine schnelle Reaktion auf Raumtemperaturänderungen. Bisherige Steuer- und Regelstrategien für TABS können nur sehr schlecht mit der thermischen Trägheit umgehen, da diese in der Regel keine Prädiktionen verwenden. Hinzu kommt eine aufwändige Parametrierung dieser TABS-Strategien, was in der Praxis zu Inbetriebnahmephasen von oft mehreren Jahren führt. Die Möglichkeit TABS als einen Kurzzeitenergiespeicher für das durch die wachsende Einspeisung aus fluktuierenden erneuerbaren Energiequellen belastete Stromnetz nutzbar zu machen, spielt bei diesen Standard-TABS-Strategien bisher keine Rolle.
In dieser Arbeit wurde ein neuartiger Algorithmus für die Steuerung von TABS entwickelt, der hier durch die Abkürzung AMLR gekennzeichnet wird. Die AMLR nutzt Vorhersagen der Hauptstörgrößen einer TABS-Zone zur Berechnung eines innerhalb des nächsten Tages zuzuführenden Energiepaketes. Zu den Hauptstörgrößen zählen die tagesgemittelte Außentemperatur, die tagesgemittelte globale Einstrahlung sowie ein Belegungsplan jeder TABS-Zone. Die AMLR verwendet ein dynamisches und ein stationäres Widerstands-Kapazitäten(RC)-Modell mit einem Verzögerungsglied erster Ordnung (PT1). Das stationäre TABS- und Raummodell wird für eine Adaptionsfähigkeit und das dynamische Modell für die zeitdiskrete Berechnung von Leistungen genutzt. Es wird gezeigt, dass die Genauigkeit eines Modells mit PT1-Glied für die Steuerung von TABS ausreichend ist. Durch die Adaptionfähigkeit kann sich der Algorithmus automatisiert an unterschiedliche Gebäude, Standorte und Nutzungsprofile anpassen. Auf die Erstellung eines Gebäudemodells inklusive dessen technischer Gebäudeausrüstung (TGA), der Wärmelasten sowie der Wettereinflüsse kann somit verzichtet werden. Weiterhin können mit der AMLR mittlere Soll-Raumtemperaturen pro TABS-Zone vorgegeben werden, was bei Standard-TABS-Strategien nicht möglich ist. Dem Autor stehen als Testumgebungen zur Evaluierung der AMLR die Triple-Klimakammer des Instituts für Energiesystemtechnik (INES) der Hochschule Offenburg sowie zwei reale Gebäude und deren Simulationsmodelle zur Verfügung. Bei den Gebäuden handelt es sich um das in Basel befindliche IWB CityCenter sowie das Seminargebäude der Hochschule Offenburg.
Mit Hilfe der Triple-Klimakammer werden die verwendeten RC-Modelle sowie das TRNSYS-Simulationsmodell der Kammer selbst validiert. Durch den direkten Vergleich der AMLR zu Standard-TABS-Strategien kann in Model-in-the-Loop (MiL) Simulationen, Laborversuchen und Pilotanlagen gezeigt werden, dass die AMLR insbesondere dann thermische Energie einsparen kann, wenn es bei der Standardstrategie zu Überhitzungen im Heizfall und Unterkühlungen im Kühlfall kommt. Des Weiteren zeigen sich Energieeinsparpotenziale durch die Möglichkeit der zonenspezifischen Beladung der TABS. Anhand von Messdaten einer Pilotanlage kann eine Reduktion des thermischen TABS-Energiebedarfs von über 41 % belegt werden. In allen Testumgebungen kann eine Einsparung an Hilfsenergie von bis zu 86 % für die TABS-Pumpen bei gleichzeitiger Verbesserung des thermischen Komforts nachgewiesen werden. Neben Energieeinsparungen sind durch den Einsatz der AMLR Investitionseinsparungen durch eine vereinfachte TABS-Hydraulik möglich, da keine konstanten Vorlauftemperaturen notwendig sind. Weiterhin kann gezeigt werden, dass die Leistung eines Zusatzkühlsystems durch den Einsatz der AMLR im Vergleich zur Standard-TABS-Strategie reduziert werden kann, ohne den thermischen Komfort zu beeinträchtigen. Anhand von Simulationsrechnungen wird das Potenzial von TABS für Lastverschiebemaßnahmen quantifiziert. Durch die Verwendung der AMLR mit dynamischen Strompreisen ist im gezeigten Beispiel eine Einsparung an monetären Kosten von 38 % möglich. Weiterhin konnten Anfragen zur Abschaltung der Beladung der TABS zum Ausgleich fluktuierender erneuerbarer Energieerzeuger durch die AMLR unter Einhaltung des thermischen Komforts durchgeführt werden.
This thesis deals with the redesign of manufacturing systems by simulation and optimization. Material flow simulation is a common tool for solving problems in system design. Limitations are the high requirements in time and knowledge to execute simulation studies, evaluate results and solve design problems. New chances arrives with the technologies of industry 4.0 and the digital shadow, providing data for simulation. However, the methods to use production data for the redesign of production systems are not available yet. Purpose of this work is providing the methods to automate simulation from digital shadow, use simulation to optimize and solve problems in system design. Two case studies are used to support the action research approach of this work. The result of this work is a framework for the application of the digital shadow in optimization and problem-solving.
Electrochemical pressure impedance spectroscopy (EPIS) has received the attention of researchers as a method to study mass transport processes in polymer electrolyte mem-brane fuel cells (PEMFC). It is based on analyzing the cell voltage response to a harmonic excitation of the gas phase pressure in the frequency domain. Several experiments with a single-cell fuel cell have shown that the spectra contain information in the frequency range typical for mass transport processes and are sensitive to specific operating condi-tions and structural fuel cell parameters. To further benefit from the observed features, it is essential to identify why they occur, which to date has not yet been accomplished. The aim of the present work, therefore, is to identify causal links between internal processes and the corresponding EPIS features.
To this end, the study follows a model-based approach, which allows the analysis of inter-nal states that are not experimentally accessible. The PEMFC model is a pseudo-2D model, which connects the mass transport along the gas channel with the mass transport through the membrane electrode assembly. A modeling novelty is the consideration of the gas vol-ume inside the humidifier upstream the fuel cell inlet, which proves to be crucial for the reproduction of EPIS. The PEMFC model is parametrized to a 100 cm² single cell of the French project partner, who provided the experimental EPIS results reproduced and in-terpreted in the present study.
The simulated EPIS results show a good agreement with the experiments at current den-sities ≤ 0.4 A cm–2, where they allow a further analysis of the observed features. At the lowest excitation frequency of 1 mHz, the dynamic cell voltage response approaches the static pressure-voltage response. In the simulated frequency range between 1 mHz – 100 Hz, the cell voltage oscillation is found to strongly correlate with the partial pressure oscillation of oxygen, whereas the influence of the water pressure is limited to the low frequency region.
The two prominent EPIS features, namely the strong increase of the cell voltage oscillation and the increase of phase shift with frequency, can be traced back via the oxygen pressure to the oscillation of the inlet flow rate. The phenomenon of the oscillating inlet flow rate is a consequence of the pressure change of the gas phase inside the humidifier and in-creases with frequency. This important finding enables the interpretation of experimen-tally observed EPIS trends for a variation of operational and structural fuel cell parame-ters by tracing them back to the influence of the oscillating inlet flow rate.
The separate simulation of the time-dependent processes of the PEMFC model through model reduction shows their individual influence on EPIS. The sluggish process of the wa-ter uptake by the membrane is visible below 0.1 Hz, while the charge and discharge of the double layer becomes visible above 1 Hz. The gas transport through the gas diffusion layer is only visible above 100 Hz. The simulation of the gas transport through the gas channel
without consideration of the humidifier becomes visible above 1 Hz. With consideration of the humidifier the gas transport through the gas channel is visible throughout the fre-quency range. The strong similarity of the spectra considering the humidifier with the spectra of the full model setup shows the dominant influence of the humidifier on EPIS.
A promising observation is the change in the amplitude relationship between the cell volt-age and the oxygen partial pressure oscillation as a function of the oxygen concentration in the catalyst layer. At a frequency where the influence of oxygen pressure on the cell voltage is dominant, for example at 1 Hz, the amplitude of the cell voltage oscillation could be used to indirectly measure the oxygen concentration in the catalyst layer.
With the increasing share of renewable energies and the nuclear phase-out, the energy transition is accelerating. From the perspective of building technology, there is great potential to support this transition given its large share in total energy consumption and the increasing number of flexible and controllable components and storages. However, a question often asked at the plant level is: "How do we use this flexibility to support the regional grid?". In this work, a grid-supportive controller of a real-world building energy plant was developed using mathematical optimisation methods and its technical feasibility was demonstrated. The results could convince actors from the energy industry and academia about the practicality of these methods and offer tools for their implementation.