Object detection and seafloor segmentation for conventional 2D side-scan sonar imagery is a well-investigated problem. However, due to recent advances in sensing technology, the side-scan sonar now produces a true 3D point cloud representation of the seafloor embedded with echo intensity. This creates a need to develop algorithms to process the incoming 3D data for applications such as object detection and segmentation, and an opportunity to leverage advances in 3D point cloud processing developed for terrestrial applications using optical sensors (e.g. LiDAR). A bottleneck in deploying 3D side-scan sonar sensors for online applications is attributed to the complexity in handling large amounts of data which requires higher memory for storing and processing data on embedded computers. The present research aims to improve data processing capabilities on-board autonomous underwater vehicles (AUVs). A supervoxel-based framework for over-segmentation and object detection is proposed which reduces a dense point cloud into clusters of similar points in a neighborhood. Supervoxels extracted from the point cloud are then described using feature vectors which are computed using geometry, echo intensity and depth attributes of the constituent points. Unsupervised density based clustering is applied on the feature space to detect objects which appear as outliers. / Master of Science / Acoustic imaging using side-scan sonar sensors has proven to be useful for tasks like seafloor mapping, mine countermeasures and habitat mapping. Due to advancements in sensing technology, a novel type of side-scan sonar sensor is developed which provides true 3D representation of the seafloor along with the echo intensity image. To improve the usability of the novel sensors on-board the carrying vehicles, efficient algorithms needs to be developed. In underwater robotics, limited computational and data storage capabilities are available which poses additional challenges in online perception applications like object detection and segmentation. In this project, I investigate a clustering based approach followed by an unsupervised machine learning method to perform detection of objects on the seafloor using the novel side scan sonar. I also show the usability of the approach for performing segmentation of the seafloor.

The importance of securing hardware, particularly in the context of the Internet of Things (IoT), cannot be overstated in light of the increasing prevalence of low-level attacks. As the IoT industry continues to expand, security has become a more holistic concern, as evidenced by the wide range of attacks that we observed, from large-scale distributed denial-of-service attacks to data theft through monitoring a device's low-level behavior, such as power consumption. Traditional software-based security measures fall short in defending against the full spectrum of attacks, particularly those involving physical tampering with system hardware. This underscores the critical importance of proactively integrating attack vectors that encompass both hardware and software domains, with a particular emphasis on considering both the analog and digital characteristics of hardware. This thesis investigates system security from a hardware perspective, specifically examining how low-level circuit behavior and architectural design choices impact SRAM's data remanence and its implications for security. This dissertation not only identifies new vulnerabilities due to SRAM data remanence but also paves the way for novel security solutions in the ongoing "security arms race". I present an attack, volt boot, that executes cold-boot style short-term data remanence in on-chip SRAM without using temperature effect. This attack exploits the fact that SRAM's power bus is externally accessible and allows data retention using a simple voltage probe. Next, I present a steganography method that hides information in the SRAM exploiting long-term data remanence. This approach leverages aging-induced degradation to imprint data in SRAM's analog domain, ultimately resulting in hidden and plausibly deniable information storage in the hardware. Finally, I show how an adversary weaponizes SRAM data remanence to develop an attack on a hardware-backed security isolation mechanism. The following provides a brief overview of the three major contributions of this thesis: 1. Volt boot is an attack that demonstrates the vulnerability of on-chip SRAM due to the physical separation common in modern SoCs' power distribution networks. By probing external power pins (to the cache) of an SoC while simultaneously shutting down the main system power, Volt boot creates data retention across power cycles. On-chip SRAM can be a safe memory when the threat model considers traditional off-chip cold-boot-style attacks. This research demonstrates an alternative method for preserving information in on-chip SRAM through power cycles, expanding our understanding of data retention capabilities. Volt boot leverages asymmetrical power states (e.g., on vs. off) to force SRAM state retention across power cycles, eliminating the need for traditional cold boot attack enablers, such as low-temperature or intrinsic data retention time. 2. Invisible Bits is a hardware steganography technique that hides secret messages in the analog domain of SRAM embedded within a computing device. Exploiting accelerated transistor aging, Invisible Bits stores hidden data along with system data in an on-chip cache and provides a plausible deniability guarantee from statistical analysis. Aging changes the transistor's behavior which I exploit to store data permanently (ie long-term data remanence) in an SRAM. Invisible Bits presents unique opportunities for safeguarding electronic devices when subjected to inspections by authorities. 3. UntrustZone utilizes long-term data remanence to exfiltrate secrets from on-chip SRAM. An attacker application must be able to read retained states in the SRAM upon power cycles, but this needs changing the security privilege. Hardware security schemes, such as ARM TrustZone, erase a memory block before changing its security attributes and releasing it to other applications, making short-term data remanence attacks ineffective. That is, attacks such as Volt boot fail when hardware-backed isolation such as TEE is enforced. UntrustZone unveils a new threat to all forms of on-chip SRAM even when backed by hardware isolation: long-term data remanence. I show how an attacker systematically accelerates data imprinting on SRAM's analog domain to effectively burn in on-chip secrets and bypass TrustZone isolation. / Doctor of Philosophy / In computing systems, hardware serves as the fundamental bulwark against security breaches. The evolution in software security has compelled adversaries to seek potential vulnerabilities in the hardware.The infamous cold boot attack exemplifies such vulnerabilities, showcasing how adversaries exploit hardware to access runtime secrets, even when cryptographic algorithms protect the system's disk. In this attack, volatile main memory (DRAM) is `frozen' at extremely cold temperatures, allowing it to retain information even when disconnected from the victim machine. Subsequently, an adversary transfers this `frozen memory' to another machine to extract the victim's secrets. This classic case is among numerous sophisticated hardware vulnerabilities identified in recent years, highlighting the evolving challenge of securing hardware against ingenious attacks. This rise in hardware-based attacks across industry and academia underscores the importance of adopting a comprehensive approach to safeguard computing systems. This approach must encompass secure processor design, ensuring a trusted distribution chain, rigorous software security vetting, and protection against runtime side-channel leakage. Consequently, there is a growing emphasis in both industry and academia on prioritizing security in design decisions. My dissertation delves into the low-level hardware behaviors, particularly focusing on the data remanence phenomena of Static Random Access Memory (SRAM). By discovering new security vulnerabilities and proposing effective mitigation strategies, this thesis contributes to the ongoing effort to fortify computing systems against evolving threats that are rooted in the hardware. SRAM stands as a ubiquitous form of volatile memory found in most processors and microcontrollers, serving as a crucial component for temporary storage of instructions and data to facilitate rapid access. By design, SRAM forgets its contents upon a processor's power cycle and defaults to a state determined by low-level circuit behavior. However, this dissertation unveils the possibility of retaining on-chip information even after power cycling, leveraging inherent low-level circuit behaviors to create data retention. This revelation exposes major security implications, resulting in the following three key contributions: Firstly, I introduce the volt boot attack, which exploits the vulnerability of on-chip SRAM, particularly to physical separation in modern System on Chip (SoC) power distribution networks. We conventionally assume that on-chip SRAM is secure against off-chip cold-boot attacks, but volt boot demonstrates the feasibility of achieving a similar state without traditional prerequisites such as low temperatures or long intrinsic data retention times. Subsequently, I propose a data hiding technique---invisible Bits, which leverages accelerated device wear out to embed data into the transistors of SRAM. This method introduces a novel form of hardware-based steganography, concealing data within the analog domain alongside digital system data. Lastly, I show how accelerated device aging can be weaponized to design a sophisticated attack aimed at extracting secrets from a Trusted Execution Environment (TEE) like ARM TrustZone. While short-term data remanence attacks such as Volt boot are rendered ineffective against hardware-backed isolation enforced by TEEs, UntrustZone harnesses the methodologies and tools from preceding works to induce long-term data remanence. This poses a new threat to on-chip cryptography that stores secrets on chip, even when fortified by hardware isolation mechanisms, such as ARM TrustZone.

No / Several recent empirical tests of the Capital Asset Pricing Model have been based on the conditional relationship between betas and market returns. This paper shows that this method needs reconsideration. An adjusted version of this test is presented. It is then demonstrated that the adjusted technique has similar, or lower, power to the more easily implemented CAPM test of Fama and MacBeth (1973) if returns are normally distributed.

No / Antipsychotic drug-induced side effects of weight gain and sexual dysfunction have clinical significance adversely affecting both compliance and morbidity. This study evaluated the effects of haloperidol and the atypical antipsychotic risperidone (0.1¿1.0 mg/kg) on weight gain, food and water intake, the oestrous cycle and uterine weight in female hooded Lister rats. Haloperidol and risperidone treated rats displayed marked weight gain, although only risperidone induced significant increases in food consumption over the 21-day period. Neither haloperidol nor risperidone influenced water consumption. Marked disruption of the oestrous cycle was observed in risperidone- and haloperidol-treated animals (0.5 and 1.0 mg/kg), which was supported by significantly reduced uterine weights. The findings presented here suggest that the weight gain and sexual dysfunction induced by antipsychotics may be modelled in rodents. This model may offer insight into the mechanisms involved in mediation of such side effects.

Yes / Current drugs against human African trypanosomiasis (HAT) suffer from several serious drawbacks. The search for novel, effective, brain permeable, safe, and inexpensive antitrypanosomal compounds is therefore an urgent need. We have recently reported that the 4-aminoquinoline derivative huprine Y, developed in our group as an anticholinesterasic agent, exhibits a submicromolar potency against Trypanosoma brucei and that its homo- and hetero-dimerization can result in to up to three-fold increased potency and selectivity. As an alternative strategy towards more potent smaller molecule anti-HAT agents, we have explored the introduction of ω-cyanoalkyl, ω-aminoalkyl, or ω-guanidinoalkyl chains at the primary amino group of huprine or the simplified 4-aminoquinoline analogue tacrine. Here, we describe the evaluation of a small in-house library and a second generation of newly synthesized derivatives, which has led to the identification of 13 side chain modified 4-aminoquinoline derivatives with submicromolar potencies against T. brucei. Among these compounds, the guanidinononyltacrine analogue 15e exhibits a 5-fold increased antitrypanosomal potency, 10-fold increased selectivity, and 100-fold decreased anticholinesterasic activity relative to the parent huprine Y. Its biological profile, lower molecular weight relative to dimeric compounds, reduced lipophilicity, and ease of synthesis, make it an interesting anti-HAT lead, amenable to further optimization to eliminate its remaining anticholinesterasic activity. / Wellcome Trust

This thesis aims towards devising a non-destructive testing methodology for ICs fabricated by a third party manufacturer to ensure the integrity of the chip. With the growing trend of outsourcing, the sanity of the final product has emerged to be a prime concern for the end user. This is especially so if the components are to be used in mission-critical applications such as space-exploration, medical diagnosis and treatment, defense equipment such as missiles etc., where a single failure can lead to a disaster. Thus, any extraneous parts (Trojans) that might have been implanted by the third party manufacturer with a malicious intent during the fabrication process must be diagnosed before the component is put to use. The inherent stealthy nature of Trojans makes it difficult to detect them at normal IC outputs. More so, with the restriction that one cannot visually inspect the internals of an IC after it has been manufactured. This obviates the use of side-channel signal(s) that acts like a signature of the IC as a means to assess its internal behavior under operational conditions. In this work, we have selected power as the side-channel signal to characterize the internal behavior of the ICs. We have used two circuit partitioning based approaches for isolating and enhancing the behavioral difference between parts of a genuine IC and one with a sequence detector Trojan in it. Experimental results reveal that these approaches are effective in exposing anomalous behavior between the targeted ICs. This is reflected as difference in power-profiles of the genuine and maligned ICs that is magnified above the process variation ensuring that the discrepancies are observable. / Master of Science

Yes / Detailed electricity load profile for domestic building is an important requirement for the accurate analysis of demand side management. The use of electrical appliances within domestic buildings varies significantly with respect to time, mainly in accordance with the activity and behaviour of the occupants. This paper presents results from a monitoring study of electrical energy consumption profiles for One UK household (two adults with children). Measurements for whole household electricity consumption have been obtained over a period of ten months. They were all obtained at one minute interval. Monthly energy consumptions, daily and overall profiles were derived for this household type from the monitored data. It is intended that the results presented in this paper can be used in the quest for a precise forecast method for electricity consumption for occupants living in the same type of household in the UK. This will allow greater confidence in the sizing of, e.g., adopting renewable energy sources in this type of household. Further investigation is needed for a large sample of households to improve the understanding of monitoring high resolution domestic energy consumption. / MSCRC

Clostridium difficile causes pseudomembranous colitis in humans and a similar ileocecitis in hamsters. This organism can colonize the intestines after antibiotic therapy disrupts the normal intestinal microflora. Once established in the intestines, the organism causes disease by producing two toxins, designated toxin A and toxin B. Only toxin A is active on intestinal epithelium, thus toxin A is the cause of the initial tissue damage in the intestines. In order for a toxin to affect a cell, it must first bind to the cell. Toxin A has been shown to bind to Galα1- 3Galβ 1-4GIcNAc on the intestinal epithelium of hamsters. I provide evidence that toxin A can use this trisaccharide as a functional receptor on cell lines, and that the expression of the carbohydrate receptor increases the sensitivity of the cells to toxin A. Furthermore, the intestinal epithelium of infant hamsters bound less toxin A at 37C than did the adult tissue, and infants are less sensitive to the disease caused by C. difficile than are adults. This provides further evidence that the activity of toxin A is increased by the binding of the toxin to Galα1-3Galβ1- 4GlcNAc. Even though Galα1-3Galβ 1-4GlcNAc was a receptor for toxin A on animal cells, it probably is not a receptor for toxin A in humans, because people do not normally express this carbohydrate. Instead, I found that toxin A bound to the carbohydrate antigens designated I, X, and Y, which are present on the intestinal epithelium of humans. These carbohydrates could be receptors for toxin A. The possible significance of these receptors is discussed. / Ph. D.

Clostridium sordellii cause gas gangrene in man and animals, and more recently it has been implicated as a causal agent of diarrhea and enterotoxemia in domestic animals. This organism was once believed to cause pseudomembranous colitis (PMC) in humans, however, Clostridium difficile, not C. sordellii, was found to be the causative agent of this disease. It is now known that C. difficile produces two toxins, designated A and B, that are implicated in the pathogenesis of the disease. C. sordellii produces two toxins, designated HT (Hemorrhagic Toxin) and LT (Lethal Toxin), that are similar to toxins A and B of C. difficile. The goal of my research was to purify and characterize the two toxins of C. sordellii, and compare their properties to those of C. difficile. Toxin HT was purified from C. sordellii (VPI strain 9048) culture filtrate by ultrafiltration through an XM-100 membrane filter and immunoaffinity chromatography using a monoclonal antibody to toxin A of C. difficile as the ligand. Toxin LT was purified to 80% homogeneity by ultrafiltration on an XM-100 membrane filter and ion-exchange chromatography. Toxin HT migrated as a major band with molecular weight of 525,000 and a minor band at 450,000 on non-denaturing PAGE. By SDS-PAGE the molecular weight was estimated at 300,000. Isoelectric focusing indicated a pI of 6.1. Like toxin A, toxin HT was cytotoxic to cultured cells, lethal for mice, and elicited an accumulation of hemorrhagic fluid in rabbit ileal loops. Toxin LT exhibited properties similar to toxin B, although LT was about a 1000-fold less cytotoxic than toxin B. By SDS-PAGE the molecular weight was estimated at 260,000. Immunodiffusion analysis revealed a reaction of partial identity between these toxins and their amino-terminal sequences were very similar. Toxins HT and LT of C. sordellii have retained remarkable immunological similarities as well as physicochemical and biological properties with toxins A and B of Q. difficult however the toxins are not identical. / Ph. D.

Von den frühen Tagen der Logfile-Analysen bis hin zur heutigen Verwendung von fortschrittlichen Tracking-Systemen wie Google Analytics hat sich die Nutzerverfolgung im Netz stetig weiterentwickelt. Doch während sie Websitebetreibern und Werbedienstleistern wertvolle Informationen liefert, wirft sie auch Fragen hinsichtlich des Privatsphäre- und Datenschutzes auf. Das Sammeln von persönlichen Daten und deren anschließende Verwendung ruft bei vielen Menschen Besorgnis hervor. Die Gesetzgeber reagieren darauf mit immer strengeren Datenschutzgesetzen, die das Aggregieren, Verarbeiten und Speichern von personenbezogenen Daten in der Webanalyse einschränken. Viele Unternehmen stehen daher vor der Herausforderung, ihre Tracking-Infrastruktur zu überdenken und an die Vorgaben anzupassen. Spätestens mit der bevorstehenden Abschaffung der sogenannten Third-Party-Cookies sind Websitebetreiber gezwungen, aktiv zu werden. Diese Arbeit zielt darauf ab, Tracking-Technologien und -Strategien hinsichtlich ihrer Zukunftssicherheit zu analysieren, um einen Kompromiss zwischen den Interessen der Gesetzgebung und den Anbietern sowie Nutzern von Tracking-Tools zu finden.:Inhaltsverzeichnis Abkürzungsverzeichnis 1. Einleitung 2. Datenschutzrechtliche Rahmenbedingungen 2.1 Geschichte des Datenschutzrechts 2.2 Die DSGVO: Auswirkungen und Grundsätze 2.3 Rechtliche Einordnung von Tracking-Technologien 3. Grundlagen des Webtrackings 3.1 Cookies 3.1.1 Funktionsweise 3.1.2 Unterscheidung nach Lebensdauer 3.1.3 Unterscheidung nach Quelle 3.1.4 Unterscheidung nach Nutzungsart 3.1.5 Third-Party-Cookies in der Kritik 3.2 Tracking-Pixel 3.3 Device Fingerprinting 3.4 Datenqualität in der Krise 4. Tracking-Strategien in der Praxis 4.1 CNAME-Cloaking 4.1.1 Implementierung 4.1.2 Risiken 4.1.3 Datenschutzrechtliche Einordnung 4.2 Server Side Tracking 4.2.1 Tagging mit dem Google Tag Manager 4.2.2 Risiken 4.2.3 Datenschutzrechtliche Einordnung 4.3 Shynet 4.3.1 Implementierung und Quellcode-Analyse 4.3.2 Risiken 4.3.3 Datenschutzrechtliche Einordnung 5. Status Quo und Ausblick 5.1 Google Consent Mode v2 5.2 Browseranbieter 5.3 Cookie Pledge 5.4 E-Privacy-Verordnung 6. Fazit Literaturverzeichnis Abbildungsverzeichnis Eigenständigkeitserklärung