Digital Commons Network^™

Spying The Lie: Insider Threat Prevention In National Security, Jazma M. Parker

Journal of Strategic Security

Insider threats pose significant risks to critical assets within the United States. The US intelligence community has already experienced the consequences of insider compromise, such as the unauthorized release of classified material to WikiLeaks and foreign adversaries. Traditional mitigation strategies have struggled to keep pace with the evolving threat landscape. This article recommends updated interventions to detect and prevent insider threats within the Department of Defense and the Intelligence Community. A review of current research and best practices reveals three targeted strategies. First, organizations must prioritize the detection and reporting of anomalous behaviors that often precede insider incidents. Achieving this …

Escalation By Algorithm, Restraint By Architecture: Pakistan’S Military Ai Divergence, Sajjad Ahmed, Ahmad Nizar Yaakub, Asma Javed

Journal of Strategic Security

Debates on military artificial intelligence (AI) remain skewed toward great power dynamics, oscillating between techno-optimist celebrations of speed and techno-pessimist warnings of collapse. This binary overlooks how middle powers, operating under nuclearized rivalry and asymmetric sanction risk, embed restraint into organizational and technical practice. This article develops Systems Restrained Realism (SRR), a framework that extends defensive realism into the machine age by theorizing restraint as a deliberate doctrinal posture rather than a symptom of incapacity. Using Pakistan as a critical case, the study draws on expert interviews, procurement manuals, and UN submissions to demonstrate how restraint is operationalized through latency …

Youtube As A Tool For Digital Diplomacy And Strategic Security: A Comparative Analysis Of Russia And Kazakhstan, Bekzat Baktybekovna Baktybekova, Elmira Kagazbaeva, Botagoz Ali

Journal of Strategic Security

In the context of growing competition in the information space, digital diplomacy is gaining key importance for the strategic security of states. This study analyzes how Russia and Kazakhstan use the YouTube platform to promote their foreign policy narratives, shape the image of the state, and strengthen digital sovereignty. Based on a qualitative analysis of 60 videos (30 for each country) published by official government channels between 2020 and 2024, differences in strategies, visual codes, tonality, and patterns of interaction with the audience were identified. The Russian approach is characterized by an aggressive narrative, antagonism to Western structures, and a …

Classified Information Management In Kosovo: Lessons From Nato, The European Union, And The Western Balkans, Bahri Gashi, Ngadhnjim Brovina, Arian Kadriu

Journal of Strategic Security

This study examines the legal framework for the protection of classified information in Kosovo, focusing on the role of the Agency for the Protection of Classified Information (APCI). The selection of APCI as the focal institution stems from its central role in implementing Kosovo’s legal and institutional framework for classified information, following the country’s efforts to align with Euro-Atlantic standards. In a newly established state like Kosovo, protecting sensitive information is crucial for national security. The study compares Kosovo’s model with those of the North Atlantic Treaty Organization (NATO), the European Union (EU), and Western Balkan countries, highlighting its alignment …

The Role Of Special Services In Providing National Information Security, Volodymyr Artemov, Alexander Rusnak, Viktor Trepak, Grygorii Ostafiichuk, Alexandr Kalinin

Journal of Strategic Security

The growing dependence of states on digital infrastructures has elevated national information security to a matter of strategic importance. This study examines the role of special services (intelligence agencies) in protecting against cyber threats, focusing on their legal, operational, and technological functions. Using a combination of comparative legal analysis, case law review, expert surveys, and statistical modelling across 20 countries, the research highlights both strengths and limitations of current approaches. The findings demonstrate that states with clear and specific legislation on intelligence and cybersecurity achieve a 26% higher rate of preventive success than those with ambiguous frameworks. Strong judicial oversight …

Public-Private Cooperation In European Cybersecurity, Andreea Nicoleta Dragomir, Daiana Maura Vesmaș

Journal of Strategic Security

This article critically examines if the public–private partnerships (PPPs) help the European Union strengthen its cyber resilience, a challenge that is now closely tied to the Union’s broader strategic security goals. The discussion does not rely on one single angle. It moves back and forth between the legal side—looking at instruments such as the Network and Information Systems 2 (NIS2) Directive, the Cybersecurity Act, the proposed Cyber Resilience Act, and the Cyber Solidarity Act—and the lessons that come from practice. Examples include the dismantling of Operation Avalanche, the experience of the European Cyber Security Challenge, and the information-sharing efforts of …

Analysis Of Security Concerns In India-Central Asia Relations, Anmol Mukhia, Anurag Tripathi, Sanjeev Kumar Tiwari

Journal of Strategic Security

India-Central Asia relations have gained strategic significance driven by its historical ties, growing economic interests, and, most importantly, evolving security dynamics. This article deals with multifaceted security concerns such as drug trafficking, terrorism, radicalization, and the implications of instability in Afghanistan. The findings show that security concerns in the region, particularly in Afghanistan and Pakistan, constitute a significant obstacle, alongside geographical challenges, to India’s connectivity with the Central Asian Republics (CARS). India’s rising aspiration to increase connectivity and build closer ties with the region in energy, trade, and commerce heavily relies on a peaceful, prosperous, and stable Central and South …

Shadow Logistics: Military Vulnerability Through Civilian Dependence, Gilles A. Paché

Journal of Strategic Security

The rapid evolution of civilian-origin technologies repurposed for defense is reshaping the foundations of logistical advantage and altering the conditions under which armed forces operate. Modern missions rely on an extensive ecosystem of infrastructures—port terminals, cloud services, data platforms, and civilian contractors—whose reliability frequently lies beyond the authority of public institutions. This environment gives rise to shadow logistics, a network of civilian systems largely absent from conventional doctrine yet capable of producing significant operational disruptions when failures occur. Case studies show that some dark assets, whether physical or informational, can act as multipliers of effectiveness while simultaneously creating systemic vulnerabilities …

Chokepoints: American Power In The Age Of Economic Warfare. By Edward Fishman. Portfolio Penguin, 2025., Mark T. Peters Ii

Journal of Strategic Security

No abstract provided.

The Russian Fsb – A Concise History Of The Federal Security Service. By Kevin Riehle. Georgetown University Press, 2024., Michael W. Parrott

Journal of Strategic Security

No abstract provided.

New Developments In Space-Filling Designs, Xiankui Yang

USF Tampa Graduate Theses and Dissertations

This dissertation presents three methodological advancements to improve the construction of space-filling designs for meeting different needs of computer experiments. Traditional space-filling designs focus on achieving uniform coverage in the input space, ensuring that design points are spread evenly throughout. However, in some scientific and engineering applications, varied density of design points may be desired for more efficient data collection when prior knowledge implies different emphases. In other cases, ensuring good coverage and/or spread of the response values allows better performance of fitted models in the next stage of applications. Many processes involve variation in response values. Therefore, incorporating variation …

Combating Β-Lactamase Resistance: From Inhibitor Design To Substrate Evolution, Lian M.C. Jacobs

USF Tampa Graduate Theses and Dissertations

β-lactamase production by bacteria is a major mechanism of antibiotic resistance. These enzymes hydrolyze β-lactam antibiotics, preventing them from binding to and inhibiting PBPs. Although new β-lactam scaffolds and inhibitors are continually introduced into the clinic, resistance often emerges within a few years. Therefore, the development of cross-class inhibitors with novel scaffolds is critical to mitigate this resistance. In parallel, a deeper understanding of the structural and mechanistic basis of β-lactamase resistance is essential. Together, these approaches provide an effective strategy for combating antibiotic resistance.

The first project addressed the need of effective cross-class β-lactamase inhibitors capable of targeting SBL …

Unquaint Pigs’ Stakeholder Perspectives On Wild Swine In Central Western Florida, Tyler Koerner

USF Tampa Graduate Theses and Dissertations

The Anthropocene presents important questions for how to address the continuous transferal of new species into new spaces and the cascading impacts of environmental transformations. Novel ecosystems present one such outline for conservation that acknowledges the modification of historic ecosystems and the social entanglements that arrive with new species. I argue that novel ecosystems can benefit from further anthropological integrations that aid in describing the entanglements of introduced species and the pursuit of best managerial outcomes. For wild swine in Florida, the adoption of a novel approach is especially relevant because of entanglements with historic and modern Floridian stakeholders and …

The Heterogeneous Response Of Astrocytes In Different Brain Regions Under Metabolic Stress, Pawan Kumar Thapaliya

USF Tampa Graduate Theses and Dissertations

Astrocytes play a central role in maintaining ionic homeostasis, neurotransmitter clearance, and brain en-ergy metabolism. Their excitability, reflected in activity-evoked intracellular sodium (Na+, [Na+]i) and calcium (Ca2+,[Ca+]i) dynamics, is increasingly recognized as a critical determinant of neuronal function and vulnerability, particularly under metabolic stress. Despite their importance, the mechanisms underlying astrocytic ionic signaling and its regional heterogeneity remain incompletely understood. In this thesis, I developed detailed computational and biophysical models to investigate astrocytic Na+ and Ca2+ dynamics, their bioenergetic consequences, and the roles of key ion transporters under physiological and metabolically stressed conditions, validating the models against experi- mental data. …

How Well Are We Preparing U.S. Youth With Down Syndrome For Health Care Transition? A Mixed-Methods Study Assessing Provider Support And Exploring Caregiver Experiences, Suman Kanti Chowdhury

USF Tampa Graduate Theses and Dissertations

Background: Health care transition (HCT) preparation is a structured process that empowers youth to take ownership of their health care as they transition into adulthood. Youth with Down syndrome (DS), a common genetic disorder associated with a high burden of co-occurring conditions, require HCT preparation support at a higher rate than their typically developing peers. Although transition preparation has been examined across various chronic conditions, few studies have focused on youth with DS. Moreover, prior research was limited by methodological constraints, including the lack of a validated HCT index, a small sample size, outdated estimates, and a lack of a …

Motivating Lung Cancer Screening Uptake: An Experimental Test Of Didactic Versus Narrative Messages For Lung Cancer Screening Among Individuals Who Currently Smoke Or Formerly Smoked, Honor M. Woodward

USF Tampa Graduate Theses and Dissertations

Lung cancer is the number one cause of cancer-related death in the United States and worldwide. Lung cancer screening with low-dose computed tomography (LDCT) has been associated with a 20% reduction in lung cancer-related mortality. Despite the obvious benefits of lung cancer screening with LDCT, screening is heavily underutilized compared to other cancer screening tests. Thus, it is critically important to develop strategies that help motivate screening uptake among eligible individuals. This study explored the effectiveness of narrative messages for motivating lung cancer screening uptake among individuals eligible for lung cancer screening who currently smoke or formerly smoked. Drawing from …

Riki&Dolphin: Real Time Data Transmission From The Bottom Of A Cave To A Website, Luca Tringali, Giacomo Canciani Dr., Tecla Tripari, Alexander Debenjak, Caterina Bearzotti

International Journal of Speleology

Coming from over 10 years of experience in cave monitoring in northeast Italy, Gruppo Speleologico Talpe del Carso, has designed Riki and Dolphin: customizable, low cost, and easy to assemble tools for getting real time data transmission from the bottom of a cave, even underwater, to a webserver. Their use has been tested to monitor air temperature inside the Abisso Bonetti Cave (Classical Karst, Italy), proving for the first time that a cave in Gorizian Karst can systematically be colder than the outdoor temperature even in winter, recording an internal temperature even lower than 0°C. The Dolphin device can be …

Hand Gesture Control For A Di2erential Drive Robot, Seyoung Kan, Laray Lopez, Zachary Hinnen, Alfredo Weitzenfeld

Bellini College REU Symposium (BCREUS)

As technology becomes increasingly integrated into daily life, seamless and multimodal human-robot interaction has become essential. This project presents a lightweight, real-time human-following system implemented on a differential-drive robot (Ham-Bot) using a Raspberry Pi, motivated by the growing need for robotic companionship among elderly and mobility-impaired individuals. The system integrates HSV-based color segmentation, MediaPipe hand gesture recognition, LiDAR-based distance regulation, and a six-state finite state machine to achieve robust human-robot interaction without relying on heavy machine learning models for body detection. A socket-based communication architecture streams camera frames from the robot to a MacOS client, where perception is performed and …

Hardware Cluster For Key Security And Education Experiments, Michelle Mcaveety, Rylan Pietras, Ahmed Ghoneim, Robert Karam

Bellini College REU Symposium (BCREUS)

In response to increased cyberattacks against digital infrastructures, significant contributions have been made to the education of software-based cybersecurity principles through online resources, coursework, and other means. However, there is a lack of accessible platforms dedicated to the learning of hardware-based cybersecurity principles. Specifically, topics such as side-channel attacks or fault injection attacks can be challenging to study without expensive hardware resources. To address this need, we propose the Hardware Cluster for Key Security and Education Experiments (HaCKSEE) platform. HaCKSEE is an experiment-oriented platform designed to democratize hardware security education. The proposed platform allows students to conduct configurable hardware security …

Neurons Of Bias: Power-Mediated Compliance And Mitigation In Large Language Models, Anubhav Gupta, Otavio Rosa, Mahammed Kamruzzaman, Gene Kim

Bellini College REU Symposium (BCREUS)

Introduction & Problem Statement

Large language models (LLMs) are increasingly deployed in sociotechnical systems involving power, authority, and compliance, raising important questions about fairness, consistency, and reliability across diverse user populations. As these systems are integrated into hiring tools, customer service systems, assistive technologies, and decision-support pipelines, they are expected to operate consistently regardless of the identity they are prompted to adopt. However, when demographic attributes are introduced into prompts, model behavior may shift even when identity does not change the underlying task.

In power-mediated settings, such variation is especially important because differences in compliance, refusal, or loophole-seeking behavior may …

Misty: An Llm-Driven Recipe Recommender Robot, Alina Pineda, Stuti Goyal, Jingjing Li, Zhao Han

Bellini College REU Symposium (BCREUS)

Introduction & Problem Statement

Meal planning requires balancing nutritional needs, available ingredients, and user preferences, which can be time-consuming and cognitively demanding. While mobile recipe applications provide personalized recommendations, they lack interactive and socially engaging communication. In contrast, social robots such as Misty enable expressive interaction through speech, gestures, and emotional cues, but typically rely on rigid, pre-programmed behaviors and lack domain-specific knowledge for tasks such as recipe recommendation.

This gap highlights the need for a system that combines the strengths of both technologies. Recipe recommendation is inherently multimodal, requiring both social interaction for engagement and visual presentation for detailed …

Strider: Human Re-Identification Using Gait Recognition, Mark Calvelo, John Pham, Aleksandre Papunashvili, Mauricio Pamplona Segundo

Bellini College REU Symposium (BCREUS)

Gait Recognition pipelines have shown promise in recent years with modern models such as SkeletonGait [1] and GPGait [2] demonstrating decent performance on known benchmarks. These Gait Recognition models utilize resource and computationally expensive pipelines for full end-to-end Gait Recognition. This overhead can prove to be a problem for real-time tasks such as on-device recognition. In this project, we aim to reduce one of the most important phases of the Gait Recognition pipeline which is Skeleton and Silhouette generation. We build off of the YOLOv11 architecture [3] simplifying aspects of the existing model to create a model that can efficiently …

Last-Mile Autonomous Delivery Robot, Lucas Araujo Bianco, Clement Joseph, Chance Hamilton, Alfredo Weitzenfeld

Bellini College REU Symposium (BCREUS)

Autonomous delivery robots require robust, real-time navigation systems to safely traverse dynamic outdoor environments like college campuses. This project presents an edge-optimized vision pipeline deployed on a resource-constrained Jetson Nano-based robot to accurately identify drivable surfaces and detect path intersections. We employ a lightweight semantic segmentation Convolutional Neural Network (LRASPP MobileNetV3-Large), initially pretrained on the Cityscapes dataset. By applying transfer learning to a manually refined, locally labeled dataset of our campus, we significantly improved feature extraction for urban textures and adapted the model to our specific use case. To ensure efficient edge deployment, the network is optimized using TensorRT [1], …

Microarchitectural Vulnerabilities And Performance Tradeoffs In Shared Scientific Computing, Zyad Abd-Elrahman, Santosh Pandey

Bellini College REU Symposium (BCREUS)

Introduction & Problem Statement

Shared scientific computing platforms are built for speed and utilization, but they create a security problem that isolation alone can't fully solve. Even with TEEs, containers, or a privilege separation in place, the hardware underneath remains a shared resource. Speculative execution, cache contention, interconnect timing, and similar microarchitectural effects can leak information or create integrity risks across protection boundaries without any malicious code involved. For CI operators running graph workloads, HPC kernels, or ML pipelines in co-tenanted systems, the threat is inherent in normal execution. The real question isn't whether these vulnerabilities exist, but it's what …

Optimizing Machine Learning Workloads Performance In Ml Accelerators, Chowdhury Nafiun Nuru, Santosh Panday

Bellini College REU Symposium (BCREUS)

This project explores how to improve the performance of machine learning systems at the kernel level. As models grow in size, efficient execution depends on reducing data movement and using limited on-chip memory effectively.

Techniques such as tiling and optimized execution order are used to improve data locality and reduce memory overhead. These approaches enable better use of fast on-chip memory and minimize costly data transfers.

Using benchmark workloads, improved scheduling strategies are shown to reduce latency by avoiding suboptimal local decisions and enabling better global execution patterns.

Overall, this work demonstrates that kernel-level optimization can significantly improve performance and …

Autonomous Indoor Mapping And Navigation Using Ros2-Based Slam On A Jetson-Powered Mobile Robot, Daniel Schagen, Mark Halim, Chance Hamilton, Alfredo Weitzenfeld

Bellini College REU Symposium (BCREUS)

This project presents the design, implementation, and evaluation of an autonomous indoor mobile robot capable of simultaneous localization and mapping (SLAM) using a ROS 2-based architecture on resource-constrained embedded hardware. The system is built on a Yahboom ROSMASTER X3 platform equipped with a Slamtec RPLidar A1, IMU, and wheel odometry, running ROS 2 Foxy on an NVIDIA Jetson Nano 4GB inside a Docker container. The primary objective is to enable the robot to autonomously map an indoor hallway environment while navigating without human intervention.

The mapping pipeline integrates slam_toolbox for occupancy grid generation, with loop closure enabled and parameters tuned …

Domain Randomization For Robot Navigation, John Hightower, Danae Ferguson, Brendon Johnson, Alfredo Weitzenfeld

Bellini College REU Symposium (BCREUS)

Reinforcement learning enables robots to learn navigation policies in simulation, but performance often degrades during real-world deployment due to the sim-to-real gap. This work investigates domain randomization as a strategy to improve transfer for a Soft Actor-Critic navigation policy trained in a maze environment. Six targeted randomization methods are implemented including obstacle layouts, LiDAR noise, motion distance, positional noise, action perturbations, and maze switching to analyze how different sources of variability affect the robot’s ability to effectively navigate a maze. Results demonstrate the extent to which the robot can effectively generalize a policy for navigation given each domain randomization method, …

An Evaluation Of Biologically-Inspired Slam Models Against Traditional Models, Colby Mullins, Asadbek Nematov, Ross Volenec, Chance Hamilton, Alfredo Weitzenfeld

Bellini College REU Symposium (BCREUS)

This research presents a comparative analysis of biologically-inspired SLAM models (RatSLAM [2], SeqSLAM [3]) versus traditional feature-based geometric SLAM (ORB-SLAM3 [1]) to establish a standardized framework for evaluating accuracy, robustness, and computational efficiency under varying environmental conditions. To ensure an equitable baseline, models are subjected to a unified testing pipeline across real-world datasets (Oxford RobotCar clear and overcast sequences) and controlled Webots simulations (day/night and seasonal centerlines) using timestamp-aligned 480p monocular PNG images. Within this pipeline, pose estimations are standardized to the TUM trajectory format, and spatial alignment and scale correction are applied via the evo evaluation library [4] to …

Investigating The Effect Of Input Modality On Reasoning In Vlms Using Zero-Shot Evaluation, Rodela Ghosh, Aviral Gupta, Ocean Monjur, Shrestha Datta, Anshuman Chhabra

Bellini College REU Symposium (BCREUS)

This project investigates how input modality affects mathematical reasoning in vision-language models (VLMs). Using 100 samples from the GSM8K benchmark, we evaluate Qwen2-VL-2B-Instruct and LLaVA-v1.6-Mistral-7B across three conditions: text-only, rendered image, and a modality mismatch condition where image and text describe different problems. Both models show substantial accuracy drops under visual input — Qwen2 falls from 55% to 30% and LLaVA from 40% to 21%. In the mismatch condition, both models follow the text modality in over 75% of cases, revealing strong text dominance when modalities conflict. These findings suggest that rendering math problems as images meaningfully impairs reasoning in …

Risa: Robotic Interface For Sit-To-Stand Assistance, Hieu Tran, Rinat Mynnakhmetov, Ricardo Frumento Sr, Yu Sun

Bellini College REU Symposium (BCREUS)

Mobility limitations in older adults are expected to become increasingly prevalent, along with the larger proportion of the world’s elderly population over the next decades [1]. Among these problems is the difficulty many elderly individuals face when transitioning from a seated to a standing pose. Loss of lower-body strength and balance makes this daily activity near impossible without assistance. To address this motor impairment, solutions were developed. For example, the Elderly Bodily Assistance Robot (E-BAR) provides body-weight support using handles, pulleys, and frames [2]. While these systems demonstrate the feasibility of robotic assistance, they present key limitations. Firstly, mechanical designs …