Digital Commons Network^™

Fully Selective Opening Secure Ibe From Lwe, Dingding Jia, Haiyang Xue, Bao Li

Research Collection School Of Computing and Information Systems

Selective opening security ensures that, when an adversary is given multiple ciphertexts and corrupts a subset of the senders (thereby obtaining the plaintexts and the senders’ randomness), the privacy of the remaining ciphertexts is still preserved. Previous selective opening secure IBE schemes encrypt messages bit-by-bit, or only achieve selective-id security. In this paper, we present the first adaptive-id, selective opening secure identity-based encryption (IBE) tightly from LWE. To achieve this, we introduce a new primitive called delegatable all-but-many lossy trapdoor functions (DABM-LTDF) and provide a generic construction that converts DABM-LTDF into an adaptive-id, selective opening secure IBE through a tight …

Learning To Identify Seen, Unseen And Unknown In The Open World: A Practical Setting For Zero-Shot Learning, Sethupathy Parameswaran, Yuan Fang, Chandan Gautam, Savitha Ramasamy, Xiaoli Li

Research Collection School Of Computing and Information Systems

As vision-language models advance, addressing the Zero-Shot Learning (ZSL) problem in the open world becomes increasingly crucial. Specifically, a robust model must handle three types of samples during inference: seen classes with visual and semantic information provided in training, unseen classes with only the semantic information in training, and unknown samples with no prior information from training. Existing methods either handle seen and unseen classes together (ZSL) or seen and unknown classes (known as Open-Set Recognition, OSR). However, none addresses the simultaneous handling of all three, which we term Open-Set Zero-Shot Learning (OZSL). To address this problem, we propose a …

Dr. Tongue: Sign-Oriented Multi-Label Detection For Remote Tongue Diagnosis, Yiliang Chen, Steven S. C. Ho, Cheng Xu, Yao Jie Xie, Wing Fai Yeung, Shengfeng He, Jing Qin

Research Collection School Of Computing and Information Systems

Tongue diagnosis is a vital tool in Western and Traditional Chinese Medicine, providing key insights into a patient's health by analyzing tongue attributes. The COVID-19 pandemic has heightened the need for accurate remote medical assessments, emphasizing the importance of precise tongue attribute recognition via telehealth. To address this, we propose a Sign-Oriented multi-label Attributes Detection framework. Our approach begins with an adaptive tongue feature extraction module that standardizes tongue images and mitigates environmental factors. This is followed by a Sign-oriented Network (SignNet) that identifies specific tongue attributes, emulating the diagnostic process of experienced practitioners and enabling comprehensive health evaluations. To …

Attackg+: Boosting Attack Graph Construction With Large Language Models, Yongheng Zhang, Tingwen Du, Yunshan Ma, Xiang Wang, Yi Xie, Guozheng Yang, Yuliang Lu, Ee‑Chien Chang

Research Collection School Of Computing and Information Systems

Attack graph construction seeks to convert textual cyber threat intelligence (CTI) reports into structuredrepresentations, portraying the evolutionary traces of cyber attacks. Even though previous research hasproposed various methods to construct attack graphs, they generally suffer from limited generalizationcapability to diverse knowledge types as well as requirement of expertise in model design and tuning.Addressing these limitations, we seek to utilize Large Language Models (LLMs), which have achieved enormoussuccess in a broad range of tasks given exceptional capabilities in both language understanding and zeroshot task fulfillment. Thus, we propose a fully automatic LLM-based framework to construct attack graphsnamed: AttacKG+. Our framework consists …

Enhanced Sample Selection With Confidence Tracking: Identifying Correctly Labeled Yet Hard-To-Learn Samples In Noisy Data, Weiran Pan, Wei Wei, Feida Zhu, Yong Deng

Research Collection School Of Computing and Information Systems

We propose a novel sample selection method for image classification in the presence of noisy labels. Existing methods typically consider small-loss samples as correctly labeled. However, some correctly labeled samples are inherently difficult for the model to learn and can exhibit high loss similar to mislabeled samples in the early stages of training. Consequently, setting a threshold on per-sample loss to select correct labels results in a trade-off between precision and recall in sample selection: a lower threshold may miss many correctly labeled hard-to-learn samples (low recall), while a higher threshold may include many mislabeled samples (low precision). To address …

The Influence Of Historical Climate Cycles On The Diversification And Demography Of Species From The Neotropical Lizard Group Anolis Chrysolepis, Tony Gamble

Biological Sciences Faculty Research and Publications

Historical shifts in climate have significantly influenced the establishment of ecosystems and the evolution of species. Phylogeographical studies integrated with niche modelling can provide insights into divergence events and demography. This study explores the evolutionary history, demographic patterns, and spatiotemporal dynamics of seven South American lizard species of the Anolis chrysolepis species group, which has been proposed to be strongly impacted by Pleistocene climatic fluctuations under the Refugia Hypothesis. We utilized mitochondrial and nuclear DNA sequences to delineate lineages, estimate divergence times, and examine demographic dynamics. Ecological niche models were employed to assess historical range shifts and identify climatic stability …

Going Green In Dermatology, Rahib K. Islam, Victoria T. Tong, Shari R. Lipner

School of Medicine Faculty Publications

No abstract provided.

End-To-End (E2e) Model-Based Systems Engineering (Mbse) Framework, Joshua Adelabu, Bhushan Lohar

Shelby Hall Graduate Research Forum Presentations

This presentation explores the latest advancements in systems engineering, with a particular focus on Model-Based Systems Engineering (MBSE). It covers key definitions, benefits, applications, and challenges associated with these methodologies, as well as analyzes current frameworks and research methodologies in the field.

Adversarial Attacks And Defense Methods In Robotic Systems, Thanh D. Le

Shelby Hall Graduate Research Forum Presentations

Presentation slides for a presentation given at the 1st annual Shelby Hall Graduate Research Forum at the University of South Alabama.

Choosing Robust Leadership: Encompassing The Best-Of-N Model And Swarm Intelligence Optimization For Heterogeneous Multiple Autonomous Unmanned Aerial Vehicle Systems, Kudamuhandiramlage Harith Kolitha Warnakulasooriya

Shelby Hall Graduate Research Forum Presentations

Presentation slides for a presentation given at the 1st annual Shelby Hall Graduate Research Forum at the University of South Alabama.

Book Vi Of The Mathematical Collection Of Pappus Of Alexandria, Translated By John B. Little, John B. Little, Pappus Of Alexandria

Holy Cross Bookshelf

Book VI of the Mathematical Collection is a collection of comments or notes about various points treated in parts of a collection of other texts sometimes known as the “Little Astronomy.” Pappus uses these works as sources and frequently quotes from them in this book. In the teaching of mathematical astronomy in late antiquity, and this would include the time of Pappus, the “Little Astronomy” is often understood to have been a follow-up to Euclid’s Elements and a preliminary to the study of the Almagest of Claudius Ptolemy (ca. 100–165 CE). The “Little Astronomy” included works by a group of …

A Heterogeneous Graph-Based Multi-Task Learning For Fault Event Diagnosis In Smart Grid, Dibaloke Chanda, Nasim Yahyasoltani

Computer Science Faculty Research and Publications

Precise and timely fault diagnosis is a prerequisite for a distribution system to ensure minimum downtime and maintain reliable operation. This necessitates access to a comprehensive procedure that can provide the grid operators with insightful information in the case of a fault event. In this paper, we propose a heterogeneous multi-task learning graph neural network (MTL-GNN) capable of detecting, locating and classifying faults in addition to providing an estimate of the fault resistance and current. Using a graph neural network (GNN) allows for learning the topological representation of the distribution system as well as feature learning through a message-passing scheme. …

A Bibliometric Analysis Of The Pygmalion Effect In Organization Studies, Perihan Senel Tekin, Fevziye Bekar, Duysal Askun Celik

Journal of Global Business Insights

This research aims to examine the literature on the Pygmalion effect, which is expressed as a self-fulfilling prophecy in the context of management organization from a bibliometric perspective. In this context, all relevant publications in the Web of Science database were scanned between 01-06.06.2024. In the first and second searches with the words Pygmalion, Pygmalion effect, Pygmalionism, management, and organization, a total of 27 research articles were subjected to content analysis within the scope of a systematic review. As a result of the content analysis, it was seen that although the Pygmalion effect has been found in …

Quantum Control And Simulation Using Hamiltonian Engineering In Solid-State Nmr, Linta Joseph

Dartmouth College Ph.D Dissertations

Lattices of dipolar coupled nuclear spins in natural crystals are large, interacting quantum systems -- ideal platforms to simulate non-equilibrium many-body dynamics. Using the magnetic resonance toolkit, which includes Dynamic Nuclear Polarization (DNP), Hamiltonian engineering, and multiple-quantum Nuclear Magnetic Resonance (NMR) experiments, we study aspects of coherent control, manipulation, and readout of the complex dynamics of the spin system in NMR quantum simulation.

First, applying Hamiltonian engineering sequences, we control the system evolution. Specifically, we use a combination of numerical simulations and NMR experiments on adamantane to evaluate and compare the performance of several known sequences that aim to suppress …

Circular Restricted Three Body Manifold Trajectories Via Koopman Operator Theory, Lindsey Langton

Master's Theses

There are a multitude of computational techniques capable of modeling the behavior of nonlinear dynamic systems over time. In the field of astrodynamics, the most frequently used tools are numerical integrators, specifically Runge-Kutta algorithms. These algorithms have successfully produced numerous two-body trajectories, as well as an increasing number of three-body trajectories when two-body dynamic models fail to produce Δv values within the realm of mission feasibility. Koopman operator theory is an alternative method for modeling nonlinear dynamic behavior that captures an approximation of a nonlinear dynamic system on a defined basis in the Hilbert space. The Koopman operator is an …

Development Of Ex-Situ Accelerated Chemical Stress Test Protocol For Common Anionic Exchange Membrane Chemistries, Michael D. Friend, Michael D. Friend

Master's Theses

The development of sustainably produced hydrogen fuel (“green hydrogen”) is key for the transition to clean energy sources. Green hydrogen is produced via water electrolysis. As with many clean energy sources, one of the major barriers for scaling water electrolysis is cost. A newer category of water electrolysis is Anionic Exchange Membrane (AEM) water electrolysis. AEM electrolysis systems have the potential to cost less as they do not require the expensive precious metal catalysts the current high preforming Proton Exchange Membrane water electrolysis technologies do. However, AEM lifetimes must be long enough to be cost competitive and AEM chemical durability …

Cubr2complexes With 3,5-Disubstituted Pyridine Ligands, Christopher Landee, Diane Dickie, Mark M. Turnbull

Chemistry

Reaction of copper(II) bromide with 3,5-dichloropyridine (3,5-Cl2py) or 3,5-dimethylpyridine (3,5-Me2py) led to the isolation of the coordination polymers catena-poly[[bis(3,5-dichloropyridine)copper(II)]-di-μ-bromido], [CuBr2(C5H3Cl2N)2]n or [CuBr2(3,5-Cl2py)2]n (1), and catena-poly[[bis(3,5-dimethylpyridine) copper(II)]-di-μ-bromido], [CuBr2(C7H9N)2]n or [CuBr2(3,5- Me2py)2]n (2), respectively. The structures are characterized by bibromidebridged chains [d(av.)Cu Cu = 3.93 (9) A ]. In 1, the chains are linked perpendicular to the a axis by non-classical hydrogen bonds and halogen bonds, while in 2, only non-classical hydrogen bonds are observed. © 2025 International Union of Crystallography. All rights reserved.

Turbulence Prediction Using Non-Linear Phase Space Analysis, Jeremy Quijano

Shelby Hall Graduate Research Forum Posters

Our research presents a novel approach for turbulence prediction in computational fluid dynamics (CFD) simulations using a non-linear phase space analysis (NLPSA) and threshold algorithm. NLPSA has been utilized in medical applications to predict seizures, as well as in cybersecurity to detect malicious control and utilization of computing systems. NLPSA uses time-series data to learn the normal operating state of the system, then sets a threshold to predict when the system becomes abnormal. Turbulence prediction is similar, such that a fluid system changes from normal to abnormal. Turbulence prediction methods currently utilize machine learning tools, such as convolutional neural networks …

Out-Of-Band Anomaly Detection For Real Time Operating Systems, Jeff K. Holifield

Shelby Hall Graduate Research Forum Posters

Real Time Operating Systems (RTOS) are increasing present throughout the industrial, business, defense, and healthcare spaces. These lightweight and efficient operating systems are designed to run on embedded, resource constrained devices, often within cyber-physical systems (CFS). A defining characteristic of RTOSs is that they are deterministic. Tasks are scheduled to run on fixed timelines within guaranteed execution windows. To accomplish tasks on time, real time software must conform to worst case execution times (WCETs) as design parameters. WCET is the maximum time a particular task can take to complete. Exceeding the WCET could cause system failure and lead to damage, …

A Framework For Design Recovery, Eric Diep

Shelby Hall Graduate Research Forum Posters

Due to the increase in diverse chip production over the past decade, reverse engineering has become a difficult and daunting task. This research will create a guideline for methods to achieve design recovery of microchip logic. To accomplish this, we plan on using hardware tools such as laser delayering and microscopy imaging. We will be focusing on the DA14580 Dialog semiconductor, commonly implemented in tile trackers, to extract information for design recovery. This implementation technique is novel due to tools that have not been performed with this type of microchip. The purpose for this research is to create a framework …

Analysis Of Forensic Techniques For Additive Manufacturing Devices, Daniel B. Miller, Brad Glisson, Mark Yampolskiy, J Todd Mcdonald

Shelby Hall Graduate Research Forum Posters

Additive Manufacturing (AM) is a set of newer computer-dependent production technologies that is seeing rapid adoption across a wide variety of industries, including defense, aerospace, automotive, and healthcare. With increased adoption comes an increased opportunity for misuse and abuse of such systems, which will lead to an increased need for Digital Forensic investigations into these platforms. This research forensically analyzes a number of AM devices to explore the options available for data acquisition as well as the impacts of hardware and software design choices on the analysis and investigation results. Hardware is investigated using Open-Source Intelligence (OSINT) sources to determine …

Polyglot File Detection For Forensics, Chase Stevens, Michael Black

Shelby Hall Graduate Research Forum Posters

Polyglot files are problematic as payloads can be hidden inside them while simultaneously evading discovery by current forensic tools. Autopsy, one of the most used forensic tools in investigations, uses known signatures of file types (e.g., headers, trailers) to identify and recover files. Polyglot files are a unique case in which files are intentionally combined with other file types to make them appear benign while still containing malicious payloads. Polyglots are possible due to combinations being considered valid in both formats. Polyglot files inherently evade detection from signature-based forensic tools and malware scanners because the tools and malware scanners are …

Using Image-Based Representation For Network Intrusion Detection, Chakriya Suon, J. Todd Mcdonald

Shelby Hall Graduate Research Forum Posters

The primary focus of our research is to evaluate the effectiveness of converting network traffic data, PCAPs, into image-based representations for anomaly-based network intrusion detection. We aim to analyze PCAPs to detect malware, or malicious software in hopes of creating a useful approach for anomaly detection against cyber threats including Advanced Persistent Threats (APTs). With the rise of cyber threats, cybersecurity continues to play a critical role in the ever-changing landscape of technology, by protecting and defending against threat agents. Our research will apply novel machine learning (ML) techniques to detect potential malware transmitted over a network effectively. The overall …

Learning Without Labels: A Self-Supervised Learning Approach For Anomaly Detection In Control Systmes, Barbara Gladney

Shelby Hall Graduate Research Forum Posters

Oil pipelines, water plant systems, and other critical infrastructure are managed and operated by industrial control systems (ICS). These systems safeguard the operations of critical infrastructures, requiring minimal disruption from cyberattacks or malfunctions. The use of anomaly detection methods in control systems (ICS) can reduce system interruptions. However, anomaly detection methods often require annotated data, which may not be available for the control system. Additionally, the datasets used for the control systems do not include sensor outputs and environmental data, resulting in a restricted view of the system. This research investigates how SSL models can be applied to different control …

Directing Sophisticated Cyberattacks On Public Water Infrastructure, Ayrton C. Purdy, Jordan Shropshire

Shelby Hall Graduate Research Forum Posters

In recent years there has been an increasing number of cyberattacks on public water generation and distribution systems. Advanced persistent attackers could usurp sensor and control systems to contaminate public drinking water. In order to conceal their malicious activity, they can manipulate sensor data flows to give the appearance of normal activity. The compromised sensors would report normal chemical levels even though unsafe water is entering the distribution system. In response, this research proposes a multi-sensor, cross-validation approach to anomaly detection. The proposed approach is designed to detect sophisticated cyberattacks which are not easily detectable using traditional cyber tools. The …

End-To-End (E2e) Mbse Framework, Joshua Adelabu, Bhushan Lohar

Shelby Hall Graduate Research Forum Posters

Principles of systems engineering (SE) possess great influence. Frameworks are generated to execute and incorporate such principles. Framework can have various architectural constructs and simultaneously consist of diverse concepts. Concepts like modularity, scalability, integration, and the balance between performance, cost, and risk are guided by SE principles as well as the manufacturability of designed systems due to the migration from mass customization to mass personalization resulting in increased complexity, and as a result need to be guided and gives rise to modularity. However, principles are not enough for effective system design and understanding. There is a need for a framework. …

Thermal Stability Analysis Of Aqueous Ionic Amines For Sustainable Co2 Capture, Li Hua Zang, Keegan Everitt, Kevin West, Brooks D. Rabideau, Breanna Dobyns, James Davis

Shelby Hall Graduate Research Forum Posters

In closed air cabin atmospheres such as those of spacecraft, CO₂ accumulation jeopardizes crew respiratory function and may gradually affect sensitive equipment, making effective air revitalization critical. Traditional CO₂ capture methods like monoethanolamine (MEA) efficiently capture CO₂ but suffer from high volatility, leading to solvent loss and unpleasant odor, as well as corrosion and degradation, requiring frequent replacement. These flaws demand eco-friendly, durable alternatives. This study addresses these limitations by exploring a series of aqueous ionic amines (AIAs), salts similar to MEA in CO₂ capture efficiency but with improved thermal stability—crucial for preventing degradation under high regeneration temperatures and prolonged …

Security Vulnerabilities Of A Field Programmable Gate Array, Kylie Arnett

Shelby Hall Graduate Research Forum Posters

The primary goal of this research is to understand and exploit the security vulnerabilities of a Field Programmable Gate Array (FPGA), at the bitstream level. This paper is working to successfully show that an FPGA can be altered via the bitstream file, and a Trojan can be inserted into the device. Once a Trojan is successfully inserted into the FPGA and activated through a certain input value, a Siamese Neural Network (SNN) will be used to test the effectiveness of Trojan detection. Followed by recording the successful flag rate to detect Trojans, which will be averaged to determine the accuracy …

Establishing A Framework For Evaluating Machine Learning Performance And Security Across Computational Ecosystems, Krista Stacey, Todd R. Andel

Shelby Hall Graduate Research Forum Posters

The rapid evolution of computational ecosystems—ranging from embedded systems and cloud platforms to hybrid and quantum architectures—has introduced new challenges in deploying machine learning (ML) applications. While cloud computing offers scalability, it comes with increased latency and security risks, whereas edge computing, such as FPGA-based systems, provides real-time processing with constrained resources. Hybrid and quantum ecosystems further complicate decision-making, requiring careful trade-offs between performance and security. This research seeks to establish a framework for evaluating ML performance and security risks across these ecosystems, forming the foundation of the Computational Performance And Security System (COMPASS) decision-support tool. The study will systematically …

Effect Of Pre-Adsorbed Species On High-Pressure Adsorption Of Methane In Zeolite 5a Using Grand Canonical Monte Carlo (Gcmc) Simulations, Kanhamardi Lao, Brooks D. Rabideau

Shelby Hall Graduate Research Forum Posters

Natural gas upgrading, which removes impurities from methane (CH4), is essential for industrial applications, including liquefied natural gas (LNG) production and power generation, as well as for residential use. Removing non-hydrocarbon impurities such as carbon dioxide (CO2), nitrogen (N2), and water vapor (H2O), among others, along with separating heavier hydrocarbon gases from raw natural gas, is required to achieve high- purity methane and prevent pipeline corrosion. Zeolite 5A is a microporous aluminosilicate material with a pore size of approximately 5 Å, containing sodium and calcium cations that balance the framework’s negative charge. Its structure offers high thermal stability and a …