Connecting the dots: Exploring backdoor attacks on graph neural networks

Deep Neural Networks (DNNs) have found extensive applications across diverse fields, such as image classification, speech recognition, and natural language processing. However, their susceptibility to various adversarial attacks, notably the backdoor attack, has repeatedly been demonstrated in recent years. The backdoor attack aims to misclassify inputs with specific trigger pattern(s) into the pre-determined label(s) by training the model on the poisoned dataset. Backdoor attacks on DNNs can lead to severe real-world consequences, e.g., a deep leaning-based classifier in a self-driving car can be backdoored to misclassify a stop sign as a speed limit sign. With an increasing of real-world data being represented as graphs, Graph Neural Networks (GNNs), a subset of the DNNs, have demonstrated remarkable performance in processing graph data. Despite their efficiency, GNNs, similar to other DNNs, are also vulnerable to backdoor attacks, which can lead to severe results, especially when GNNs are applied in security-related scenarios. Although backdoor attacks have been extensively studied in the image domain, we still need dedicated efforts for the graph domain due to the difference between graph data and other data, e.g., images. This thesis embarks on an exploration of backdoor attacks on GNNs. Chapter 2 focuses on designing and investigating backdoor attacks on centralized GNNs. Specifically, we explore the influence of trigger injecting position on the backdoor attack performance on GNNs. To explore this impact, we propose approaches based on explanation techniques on GNNs, which contributes to exploring the interaction between the explainability and robustness of GNNs. Furthermore, we design a clean-label backdoor attack on GNNs to make the poisoned inputs more challenging to be detected. Considering the growing privacy concern, we focus on backdoor attacks on federated GNNs in Chapter 3. We propose a label-only membership inference attack on GNNs in the scenario that the attacker can only get label output from the GNN models. Moreover, we investigate centralized and distributed backdoor attacks on federated GNNs. Besides designing efficient backdoor attacks on GNNs, we also explore the possibility of leveraging backdoor attacks for defensive purposes for GNNs. Chapter 4 introduces a watermarking framework for GNNs based on backdoor attacks. Our research outcomes will deepen the understanding of backdoor attacks on GNNs and push the GNN model designers to develop more secure models.Cyber Securit

Is this network proper forest-based?

In evolutionary biology, networks are becoming increasingly used to represent evolutionary histories for species that have undergone non-treelike or reticulate evolution. Such networks are essentially directed acyclic graphs with a leaf set that corresponds to a collection of species, and in which non-leaf vertices with indegree 1 correspond to speciation events and vertices with indegree greater than 1 correspond to reticulate events such as gene transfer. Recently forest-based networks have been introduced, which are essentially (multi-rooted) networks that can be formed by adding some arcs to a collection of phylogenetic trees (or phylogenetic forest), where each arc is added in such a way that its ends always lie in two different trees in the forest. In this paper, we consider the complexity of deciding whether a given network is proper forest-based, that is, whether it can be formed by adding arcs to some underlying phylogenetic forest which contains the same number of trees as there are roots in the network. More specifically, we show that it is NP-complete to decide whether a tree-child network with m roots is proper forest-based, for each m≥2. Moreover, for binary networks the problem remains NP-complete when m≥3 but becomes polynomial-time solvable for m=2. We also give a fixed parameter tractable (FPT) algorithm, with parameters the maximum outdegree of a vertex, the number of roots, and the number of indegree 2 vertices, for deciding if a semi-binary network is proper forest-based. A key element in proving our results is a new characterization for when a network with m roots is proper forest-based in terms of certain m-colorings.Discrete Mathematics and Optimizatio

Radiation resistant metal–organic frameworks for the production of high specific activity 51Cr by the Szilard-Chalmers effect

Chromium-51 (51Cr) is an attractive radionuclide for diagnosis, which is usually applied for red cells and platelet radiolabeling. However, commercially available 51Cr produced in nuclear reactors via neutron activation requires long irradiation times and complex separation methods. In this work, five metal–organic frameworks (MIL-100 (Cr), MIL-100 (Fe), MIL-100 (Al), MIL-101 (Cr) and aluminium fumarate MOF (FuAl)) were synthesized and the effect of gamma ray irradiation with a high dose rate and a maximum dose of 6 MGy was investigated. The two chromium-based MOFs, MIL-100 (Cr) and MIL-101 (Cr), were selected as radiation targets to produce high specific activity 51Cr by the Szilard-Chalmers effect. A solid–liquid extraction was applied to extract the produced 51Cr under different conditions, including different extractants, extraction times and pH. The most promising results were achieved when using irradiated MIL-101 (Cr) and EDTA as extracting agent, reaching an enrichment factor of 1132 ± 50.RST/Applied Radiation & Isotope

Changes in commuting mode and the relationship with psychological stress: A quasi-longitudinal analysis in urbanizing China

Emerging longitudinal research on the relationship between commuting mode and psychological wellbeing draws exclusively from cities in developed countries and the findings are not consistent. Our study contributes to the evidence base from urban China, where rapid urban growth has raised great concerns for urbanites’ commuting problems and psychological stress risks. Drawing upon the China Health and Nutrition Survey (2006–2015), we followed a quasi-longitudinal design to examine changes in commuting mode and the associations with long-term psychological stress. Crucially, the neighbourhood-level urbanicity scale was incorporated to analyse geographic variations in the commuting-stress relationship over time. The results show that maintaining car commuting and long-duration active commuting were associated with lower levels of psychological stress, while long-duration motorised commuting trips by car or public transport were predictive of higher stress levels. Moreover, high-urbanicity areas involved more active commuting trips and short motorised commuting trips, which were beneficial to long-term psychological wellbeing. In contrast, the commuting-related stress risks were noticeable in medium urbanicity areas, where the commuting duration by public transport was extremely high. Based on the socio-institutional context of urban growth in China, we recommend that urban governments should change the focus from expanding urban development land to improving urban amenities and urbanites’ wellbeing.Urban StudiesUrbanis

Hydrodynamics for the integration of fermentation and separation in the production of diesel and jet biofuels

Over the years, various technologies have been developed to produce and separate advanced biomolecules. These technologies range from complex terpenoids for pharmaceuticals and flavors to commodity chemicals and fuels via the fermentative route. These compounds are often poorly water soluble, phase splitting organic compounds or inhibitory and unstable necessitating addition of an extractive, second liquid phase for product removal. The turbulent conditions in the multiphasic fermentation coupled with the presence of surface-active compounds in the medium create a stable emulsion that is difficult to separate in conventional systems. Technologies such as centrifugation and de-emulsifiers have been used to separate the emulsion and recover the product. However, these type of recovery processes are expensive, drastically increase the final product’s environmental footprint and often hamper cell recycling.BT/Bioprocess Engineerin

Analysis of improved digital filter inflow generation methods for compressible turbulent boundary layers

We propose several enhancements to improve the accuracy and performance of the digital filter turbulent inflow generation technique and assess their efficacy in the context of wall-resolved large-eddy simulations of a compressible turbulent boundary layer. Improvements of accuracy include a more realistic correlation function for the transversal directions, target length scales that vary with wall-distance, and a counter-intuitive approach that involves the suppression of streamwise velocity fluctuations at the inflow. For improving the computational performance, we propose to generate the inflow data in parallel in single precision and at a prescribed time interval based on the turbulence time scale, and not at every time-step of the simulation. Based on the results of 7 wall-resolved large-eddy simulations, we find that the new correlation functions and the considered performance improvements are beneficial and therefore desired. Suppressing streamwise velocity fluctuations at the inflow leads to the fastest relaxation of the pressure fluctuations; however, this approach increases the adaptation length defined in terms of compliance with the von Kármán integral equation. The adaptation length can be shortened by artificially increasing the wall-normal Reynolds stresses, thereby preserving the desired turbulence kinetic energy level. A detailed inspection of the Reynolds stress transport budgets reveals that the observed spurious spatial transients are largely driven by pressure-related terms. For instance, increased values of u′p′¯ are found throughout the computational domain when a physical Reynolds stress distribution is prescribed at the inflow. Therefore, efforts to enhance digital filter techniques should aim at modeling pressure fluctuations as well as their correlation with the velocity components.Aerodynamic

Design and Analysis of Macro-Economic Models in the Laplace Domain: An Economic-Engineering Approach

In this thesis, we demonstrate the efficiency of Laplace domain techniques for the design and analysis of economic systems. To make the techniques applicable to economic modeling, we establish the economic analogs to the various tools and nomenclature in the engineering literature. We show that the Laplace domain provides an alternative description of economic systems, offering insights into behavior not apparent in the time domain. This allows economic discounting and cycles to be efficiently analyzed using pole-zero maps, Bode plots, and similar techniques. In addition, we demonstrate that transforming the linear differential equations of economic engineering into algebraic equations in the Laplace domain simplifies the design of economic systems.We use the Laplace domain techniques to design and analyze a macroeconomic model. By designing the model in the Laplace domain, we are able to integrate supply chain dynamics and the housing market using two-port network theory.By analyzing the model using a pole-zero map, we show that the economy's discount rates and business cycles are represented by complex poles and the economy's transmission blocking rates by complex zeros. Additionally, we demonstrate that the Bullwhip effect, a supply chain phenomenon, can be intuitively visualized using a Bode plot. These applications illustrate how Laplace-domain techniques enable the efficient design and analysis of economic systems.Mechanical Engineering | Systems and Contro

An analysis of Java release practices on GitHub

This paper examines the release practices of Java Maven Repositories on GitHub. Most prior research in this vein has been done on Maven Central, the largest Maven package repository. However, GitHub hosts 15.5 million Java repositories, and is left untapped. Additionally of interest is the fact that GitHub provides a competitor to Maven Central, GitHub packages. To this end, the paper establishes an index of all Java repositories on GitHub. Furthermore, this dataset also includes Maven configuration (POM.xml) files. Additionally, an in-depth analysis is done of a sample of 500 000 of those 15.5 million repositories. This sample ended up containing 170 798 Java Maven repositories that had those POM.xml files. In this sample we discovered that of those 170 798, 6 507 (≈ 3.8%) had set up distribution configuration. Maven Central ended up being the most popular but GitHub packages and others ended up being quite popular as well. In the external repositories configured in those Java projects we notice a distinct lack of GitHub packages, other repositories were still present. We theorize that the lower popularity of GitHub packages is because it requires authentication, which is not trivial to set up. We discuss several approaches that can improve this situation.CSE3000 Research ProjectComputer Science and Engineerin

A Toolkit To Spark Interest In Engineering Among Young Adults

This project aims to introduce engineering in a way that captures students' interest. In order to motivate studernts to try it out, instead of limited by their past experience. Therefore, expanding the original knowledge of engineering during the design ideation process becomes crucial. Beginning with the identification of factors contributing to the underrepresentation of female students in the field. Additionally, this study collaborates with Cities of Things Lab 010, which strives to incorporate citizens' opinions into the neighbourhood robot design process. Hosting the workshop and making robot development accessible to all citizens. For me, I narrowed down the scope to focus on students. To address the research questions, I conducted a literature review and identified two gaps: limited research on gender learning in STEM for ages above 18 and a scarcity of studies on the male perspective. I conducted surveys to address these gaps. One focused on the educational robotics toolkit, utilizing experiences of female Industrial Design Engineering (IDE) bachelor students (aged 18 to 21). The other survey aimed to understand the male perspective on the current situation in the engineering field. Involving both males and females in crafting the solution creates awareness of the responsibility that everyone plays a role in this situation. It is crucial to emphasize that this thesis does not aim to generate conflict between genders. Instead, its message has the ambition of shaping a world where everyone can choose what they want to do based on their interests, free from gender stereotypes. Furthermore, I defined the design goal of the toolkit based on this message.The design goal of the toolkit is to make everyone feel involved and comfortable to share their opinion in the group discussion. Encouraging the incorporation of different viewpoints and getting inspired by other people’s ideas. Ultimately, broadens the existing original impression of robotics. To visualise the design goal and validate the final concept, I developed a prototype of an inspirational toolkit with fellow students mainly from the DP3 course in the IDE bachelor program. Since the group assignment of the DP3 course is to design a cleaning robot for the campus. Utilising this toolkit to inspire students in the early stages of robot design can have a positive impact on the design process. I conducted multiple user testings to improve the prototype, considering the interplay of aesthetics, form, user experience and assembly.Final design HiveMind, I conducted user testing with a group of students to validate whether the after-use effect of the prototype aligns with the design goal. All participants agreed that they feel encouraged and comfortable expressing their ideas, and the toolkit helps them get on the same page. Furthermore, the toolkit improves group discussions in the early stages of the design process, especially when everyone in the group is not familiar with each other. The validation result shows that each participant has a more diverse impression of robots after using the toolkit. However, I observed that the shape of the robot they drew for the assignment still adheres to a traditional representation of how a robot should be. This suggests that future design recommendations could focus on the relationship between picture cognitive association, the impact of different game rules, and using the toolkit before or after hands-on activities.Integrated Product Desig

Isolating a Tree’s Skeleton using a 3-Dimensional Reconstruction

L-Systems allow for the efficient procedeural generation of trees to be used for rendering in video games and simulations. Currently, however, it is difficult to engineer grammars that mimic the behaviours of real life trees in 3 dimensions. To be able to deduce them, the skeleton of a tree can be used to train a model and generate an L-system for a given tree in particular. The aim of this paper is to provide a pipeline to isolate these skeletons from images of a tree, using Neural Radiance Fields (NeRFs) to reconstruct the tree, and using Laplacian Based Contraction to retrieve the underlying skeleton. We find that this approach leads to 3-dimensional topologies that very closely resemble the given tree.CSE3000 Research ProjectComputer Science and Engineerin