A Design Science Approach To Investigating Decentralized Identity Technology, Janelle Krupicka

Cybersecurity Undergraduate Research Showcase

The internet needs secure forms of identity authentication to function properly, but identity authentication is not a core part of the internet’s architecture. Instead, approaches to identity verification vary, often using centralized stores of identity information that are targets of cyber attacks. Decentralized identity is a secure way to manage identity online that puts users’ identities in their own hands and that has the potential to become a core part of cybersecurity. However, decentralized identity technology is new and continually evolving, which makes implementing this technology in an organizational setting challenging. This paper suggests that, in the future, decentralized identity …

Pyroscan: Wildfire Behavior Prediction System, Derek H. Thompson, Parker A. Padgett, Timothy C. Johnson

ATU Scholars Symposium

During a wildfire, it is of the utmost importance to be updated about all information of the wildfire. Wind speed, wind direction and dry grass often works as fuel for the fire allowing it to spread in multiple directions. These different factors are often issues for any firefighting organization that is trying to help fight the fire. An uncontrolled wildfire is often a threat to wildlife, property, and worse, human and animal lives. In our paper, we propose an artificial intelligence (AI) powered fire tracking and prediction application utilizing Unmanned Aerial Vehicles (UAV) to inform fire fighters regarding the probability …

Enhancing Disease Detection In South Asian Freshwater Fish Aquaculture Through Convolutional Neural Networks, Hayin Tamut, Musfikur Rahaman, Dr. Robin Ghosh

ATU Scholars Symposium

Aquaculture expansion necessitates innovative disease detection methods for sustainable production. This study investigates the efficacy of Convolutional Neural Networks (CNNs) in classifying diseases affecting South Asian freshwater fish species. The dataset comprises 1747 images representing 7 class, healthy specimens and various diseases: bacterial, fungal, parasitic, and viral. The CNN architecture includes convolutional layers for feature extraction, max-pooling layers for down sampling, dense layers for classification, and dropout layers for regularization. Training employs categorical cross-entropy loss and the Adam optimizer over 30 epochs, monitoring both training and validation performance. Results indicate promising accuracy levels, with the model achieving 92.14% and test …

Predictive Ai Applications For Sar Cases In The Us Coast Guard, Joshua Nelson

Cybersecurity Undergraduate Research Showcase

This paper explores the potential integration of predictive analytics AI into the United States Coast Guard's (USCG) Search and Rescue Optimal Planning System (SAROPS) for deep sea and nearshore search and rescue (SAR) operations. It begins by elucidating the concept of predictive analytics AI and its relevance in military applications, particularly in enhancing SAR procedures. The current state of SAROPS and its challenges, including complexity and accuracy issues, are outlined. By integrating predictive analytics AI into SAROPS, the paper argues for streamlined operations, reduced training burdens, and improved accuracy in locating drowning personnel. Drawing on insights from military AI applications …

Enhancing Cyber Resilience: Development, Challenges, And Strategic Insights In Cyber Security Report Websites Using Artificial Inteligence, Pooja Sharma

Harrisburg University Dissertations and Theses

In an era marked by relentless cyber threats, the imperative of robust cyber security measures cannot be overstated. This thesis embarks on an in-depth exploration of the historical trajectory and contemporary relevance of penetration testing methodologies, elucidating their evolution from nascent origins to indispensable tools in the cyber security arsenal. Moreover, it undertakes the ambitious task of conceptualizing and implementing a cyber security report website, meticulously designed to fortify cyber resilience in the face of ever-evolving threats in the digital realm.

The research journey commences with an insightful examination of the historical antecedents of penetration testing, tracing its genesis in …

The Role Of Attention Mechanisms In Enhancing Transparency And Interpretability Of Neural Network Models In Explainable Ai, Bhargav Kotipalli

Harrisburg University Dissertations and Theses

In the rapidly evolving field of artificial intelligence (AI), deep learning models' interpretability

and reliability are severely hindered by their complexity and opacity. Enhancing the

transparency and interpretability of AI systems for humans is the primary objective of the

emerging field of explainable AI (XAI). The attention mechanisms at the heart of XAI's work

are based on human cognitive processes. Neural networks can now dynamically focus on

relevant parts of the input data thanks to these mechanisms, which enhances interpretability

and performance. This report covers in-depth talks of attention mechanisms in neural networks

within XAI, as well as an analysis …

Decoding The Future: Integration Of Artificial Intelligence In Web Development, Dhiraj Choithramani

Harrisburg University Dissertations and Theses

The thesis explores AI's profound impact on web development, particularly in front-end and back-end processes. AI revolutionizes UI prototyping by automating design creation, enhancing both efficiency and aesthetics. It also aids in code review, content generation, and process flow experimentation, streamlining development workflows. Through AI-driven tools like GitHub's Copilot and Wix ADI, developers benefit from coding assistance and innovative design capabilities. Despite some challenges, AI's evolving role promises to reshape web development, offering unprecedented efficiency and user-centric solutions.

Enhancing Information Architecture With Machine Learning For Digital Media Platforms, Taylor N. Mietzner

Honors College Theses

Modern advancements in machine learning are transforming the technological landscape, including information architecture within user experience design. With the unparalleled amount of user data generated on online media platforms and applications, an adjustment in the design process to incorporate machine learning for categorizing the influx of semantic data while maintaining a user-centric structure is essential. Machine learning tools, such as the classification and recommendation system, need to be incorporated into the design for user experience and marketing success. There is a current gap between incorporating the backend modeling algorithms and the frontend information architecture system design together. The aim of …

In-Depth Examination Of Gas Consumption In E-Will Smart Contract: A Case Study, Manal Mansour, May Salama, Hala Helmi, Mona F.M Mursi

Journal of Engineering Research

In recent years, blockchain technology, coupled with smart contracts, has played a pivotal role in the development of distributed applications. Numerous case studies have emerged, showcasing the remarkable potential of this technology across various applications. Despite its widespread adoption in the industry, there exists a significant gap between the practical implementation of blockchain and the analytical and academic studies dedicated to understanding its nuances.

This paper aims to bridge this divide by presenting an empirical case study focused on the e-will contract, with a specific emphasis on gas-related challenges. By closely examining the e-will contract case study, we seek to …

The Role Of Artificial Intelligence In Determining The Criminal Fingerprint, Saeed Al Matrooshi

Journal of Police and Legal Sciences

The research aimed to identify the motives and justifications for the use of artificial intelligence in predicting crimes, to explain the challenges of artificial intelligence algorithms, the risks of bias and their ethical rules, and to highlight the role of artificial intelligence in identifying the criminal fingerprint during the detection of crimes. The research relied on the analytical approach, for the purpose of identifying the motives and justifications for the use of intelligence. Artificial intelligence in crime detection, explaining the challenges of artificial intelligence algorithms, their risks of bias, and ethical rules, and exploring how artificial intelligence technology can hopefully …

Securing Edge Computing: A Hierarchical Iot Service Framework, Sajan Poudel, Nishar Miya, Rasib Khan

Posters-at-the-Capitol

Title: Securing Edge Computing: A Hierarchical IoT Service Framework

Authors: Nishar Miya, Sajan Poudel, Faculty Advisor: Rasib Khan, Ph.D.

Department: School of Computing and Analytics, College of Informatics, Northern Kentucky University

Abstract:

Edge computing, a paradigm shift in data processing, faces a critical challenge: ensuring security in a landscape marked by decentralization, distributed nodes, and a myriad of devices. These factors make traditional security measures inadequate, as they cannot effectively address the unique vulnerabilities of edge environments. Our research introduces a hierarchical framework that excels in securing IoT-based edge services against these inherent risks.

Our secure by design approach prioritizes …

Parallel Algorithm For Testing The Singularity Of An N-Th Order Matrix, Ehab Alasadi

Al-Bahir

Analyze the possibilities of implementing a parallel algorithm to test the singularity of the N-th order matrix. Design and implement in ( C/C++) a solution based on sending messages between nodes using the PVM system library. Distribute the load among the nodes such that the computation time is as small as possible. Find out how the execution time and calculation acceleration depend on the number of nodes and the size of the problem (indicate the table and graphs). Based on the results, estimate the communication latency, for what size the task is (well) scalable on the given architecture, and what …

Alice In Cyberspace 2024, Stanley Mierzwa

Center for Cybersecurity

‘Alice in Cyberspace’ Conference Nurtures Women’s Interest, Representation in Cybersecurity

Immersive Framework For Designing Trajectories Using Augmented Reality, Joseph Anderson, Leo Materne, Karis Cooks, Michelle Aros, Jaia Huggins, Jesika Geliga-Torres, Kamden Kuykendall, David Canales, Barbara Chaparro

Publications

The intuitive interaction capabilities of augmented reality make it ideal for solving complex 3D problems that require complex spatial representations, which is key for astrodynamics and space mission planning. By implementing common and complex orbital mechanics algorithms in augmented reality, a hands-on method for designing orbit solutions and spacecraft missions is created. This effort explores the aforementioned implementation with the Microsoft Hololens 2 as well as its applications in industry and academia. Furthermore, a human-centered design process and study are utilized to ensure the tool is user-friendly while maintaining accuracy and applicability to higher-fidelity problems.

Case Studies Of Restapi And Graphql Architectures, Janni Daniel Balraj, Gary Clynch

Academic Poster Collection

The adoption of microservices architecture has experienced significant growth, driven by its appeal in terms of modularity, scalability, and deployment ease. However, this proliferation of microservices has intensified the demand for efficient data exchange among them. While REST API has long been the standard protocol for microservices communication, its limitations in flexibility and performance have spurred the ascent of GraphQL as a more efficient alternative, as highlighted by studies comparing their performance. As the number of microservices continues to rise, traditional methods like REST APIs prove challenging, leading to issues such as over-fetching or under-fetching of data. GraphQL addresses these …

Ai And Workforce Development: A Comparative Analysis Of Skill Gaps And Training Needs In Emerging Economies, Gursahildeep Singh Sidhu, Md Abu Sayem, Nazifa Taslima, Ahmed Selim Anwar, Fariba Chowdhury, Manataka Rowshon

Finance, Economics, and Data Analytics

AI is developing quickly and offers considerable prospects for economic development; nevertheless, it presents crucial challenges for instance, skills development and its effect on employee's jobs in developing economies. This research will seek to establish the current state of AI related skills deficits and training in these economies to establish how governments and organizations can close the gaps by preparing the workforce for the future AI revolution. In line with the research questions, the following emerges as the research problem: To what extent have emerging market companies embraced AI? What key skills are scarce both in the internal and external …

Adaptive Beyond Von-Neumann Computing Devices And Reconfigurable Architectures For Edge Computing Applications, Mousam Hossain

Graduate Thesis and Dissertation 2023-2024

The Von-Neumann bottleneck, a major challenge in computer architecture, results from significant data transfer delays between the processor and main memory. Crossbar arrays utilizing spin-based devices like Magnetoresistive Random Access Memory (MRAM) aim to overcome this bottleneck by offering advantages in area and performance, particularly for tasks requiring linear transformations. These arrays enable single-cycle and in-memory vector-matrix multiplication, reducing overheads, which is crucial for energy and area-constrained Internet of Things (IoT) sensors and embedded devices.

This dissertation focuses on designing, implementing, and evaluating reconfigurable computation platforms that leverage MRAM-based crossbar arrays and analog computation to support deep learning and error …

Addressing Challenges In Utilizing Gpus For Accelerating Privacy-Preserving Computation, Ardhi Wiratama Baskara Yudha

Graduate Thesis and Dissertation 2023-2024

Cloud computing increasingly handles confidential data, like private inference and query databases. Two strategies are used for secure computation: (1) employing CPU Trusted Execution Environments (TEEs) like AMD SEV, Intel SGX, or ARM TrustZone, and (2) utilizing emerging cryptographic methods like Fully Homomorphic Encryption (FHE) with libraries such as HElib, Microsoft SEAL, and PALISADE. To enhance computation, GPUs are often employed. However, using GPUs to accelerate secure computation introduces challenges addressed in three works.

In the first work, we tackle GPU acceleration for secure computation with CPU TEEs. While TEEs perform computations on confidential data, extending their capabilities to GPUs …

Towards Performance Guarantee For Federated Computing, Stoddard A. Rosenkrantz

Computer Science and Engineering Dissertations - Archive

In federated computing environments, where multiple independent devices collaborate without centralized resource control, ensuring reliable and predictable performance is crucial for meeting Service Level Objectives (SLOs). This dissertation presents a novel framework for achieving SLOs by utilizing measured subtask response times, which are obtained and processed locally on the client devices. Each device generates a performance curve based on its subtask response times, and only the essential parameters of this curve are transmitted to a centralized client selector. The client selector then uses these parameters to determine which devices are best suited to meet predefined SLOs for specific tasks, ensuring …

A Few-Shot Multi-Modality Traversability Segmentation Framework For Indoor Robotic Navigation, Qiyuan An

Computer Science and Engineering Dissertations - Archive

Traversability in autonomous robotic navigation refers to the ability of an autonomous agent to safely navigate over a given terrain. It plays a critical role in enabling robots to navigate over unseen or unknown terrains. Traversability segmentation aims to find an arbitrary-shaped mask covering the traversable regions (termed free-space). Current research for traversability segmentation can be divided into two scenarios: outdoor and indoor environments. Compared to the outdoor environments mainly consists of paved roads, indoor environments present unique challenges for traversability segmentation, because of diverse lighting conditions, glass doors, various floor colors and textures, arbitrary shaped appliances and furniture, presence …