Other Computer Sciences Commons^™

Escaping Isolation: An Analysis Of Virtual Machine And Container Breakout Vulnerabilities, Felix Iov

Cybersecurity Undergraduate Research Showcase

Cloud computing providers rely on multi-tenant architectures to maximize resource efficiency. This infrastructure depends on virtualization, which provides isolation between clients. This comes primarily in the form of Virtual Machines (VMs) and Containers. However, “breakout attacks” or “escapes” are a critical threat where attackers bypass these isolation layers to gain unauthorized access to the host system and neighboring environments. This paper surveys virtualization escape threats and analyzes three case studies: a runc container escape (Leaky Vessels), a VMware ESXi VM escape (VSOCKPuppet), and an NVIDIA GPU container escape (NVIDIAScape). Each demonstrates different attack surfaces, including file descriptor misuse, kernel driver …

Foreword, Pedagogical Innovations In Computer Science Education, Helen Crompton

STEMPS Faculty Publications

[Introduction] Computer science education sits at a defining moment. Across schools and universities worldwide, computing is no longer a niche discipline reserved for a select few. It is a foundational literacy that shapes how learners understand the world, participate in society, and imagine their futures. At the same time, the rapid pace of technological change, particularly in artificial intelligence, data systems, and intelligent tools, has placed unprecedented pressure on educators to rethink not only what we teach, but why and how we teach it. This book arrives precisely when such reflection is most needed.

Sociohydrodynamics: Data-Driven Modeling Of Social Behavior, Daniel S. Seara, Jonathan Colen, Michel Fruchart, Yael Avni, David G. Martin, Vincenzo Vitelli

Data Science Faculty Publications

Living systems display complex behaviors driven by physical forces as well as decision-making. Hydrodynamic theories hold promise for simplified universal descriptions of socially generated collective behaviors. However, the construction of such theories is often divorced from the data they should describe. Here, we develop and apply a data-driven pipeline that links micromotives to macrobehavior by augmenting hydrodynamics with individual preferences that guide motion. We illustrate this pipeline on a case study of residential dynamics in the United States, for which census and sociological data are available. Guided by Census data, sociological surveys, and neural network analysis, we systematically assess standard …

36 - Investigation Of The Digital Footprint Of Scientific Research In Social Media – Preliminary Findings, Lee Logan, Dominik Soos, Sean Baker, Jian Wu

Undergraduate Research Symposium

Title: Investigation of The Digital Footprint of Scientific Research in Social Media – Preliminary Findings

Authors: Lee Logan, Sean Baker, Dominik Soos, Jian Wu

The spread of scientific information and research beyond the confines of academic institutions plays a central role in how the public understands and trusts modern sciences. Social media has become an essential means of dissemination for scholarly news, papers, and other forms of engagement. This research aims to explore how scientific research is disseminated over social media to understand its role as a bridge between peer-reviewed research and the public's overall understanding. To support the research …

Bridging The Gap: Understanding And Mitigating Csrf Threats In Service Worker Environments, Sivakanesan Dhanushkanda, Mustafa A. Ibrahim

Graduate Student Government Association Research Conference

Progressive Web Applications (PWAs) are gaining popularity due to their rich features. Service Workers (SWs), one of its integral components, make this possible by providing users with offline functionality, improved performance, and effective caching techniques. SWs act as proxies positioned between the client browser and the web server, capable of intercepting requests and responses. Recent research has revealed that, despite being designed with security in mind, there are ways to circumvent these security precautions and launch various attacks.

Sensitive functions in JavaScript are functions that can introduce security vulnerabilities if not properly coded or validated. These functions can manipulate the …

Computer Science For Middle School (Cs4ms), Melani Loney, Lisa Steffian, Tancy J. Vandecar-Burdin

Center for Educational Partnerships Publications

This session will discuss the project Computer Science for Middle School and the associated findings. This Virginia Department of Education funded project provides computer science Professional Development opportunities for in-service teachers, located in Southeastern Virginia, who instruct students in middle school grades 6- 8. Participating teachers learn to integrate computer science standards into core and elective content through online, asynchronous microcredentials and in-person Summer Workshops. The presentation will include project findings and next steps including teacher efficacy for implementing the computer science standards before and after completing the microcredentials and their students’ attitudes about computer science.

Data Profits Vs. Privacy Rights: Ethical Concerns In Data Commerce, Amiah Armstrong

Cybersecurity Undergraduate Research Showcase

In today’s digital age, the collection and sale of customer data for advertising is gaining a growing number of ethical concerns. The act of amassing extensive datasets encompassing customer preferences, behaviors, and personal information raises questions of its true purpose. It is widely acknowledged that companies track and store their customer’s digital activities under the pretext of benefiting the customer, but at what cost? Are users aware of how much of their data is being collected? Do they understand the trade-off between personalized services and the potential invasion of their privacy? This paper aims to show the advantages and disadvantages …

Rising Threat - Deepfakes And National Security In The Age Of Digital Deception, Dougo Kone-Sow

Cybersecurity Undergraduate Research Showcase

This paper delves into the intricate landscape of deepfakes, exploring their genesis, capabilities, and far-reaching implications. The rise of deepfake technology presents an unprecedented threat to American national security, propagating disinformation and manipulation across various media formats. Notably, deepfakes have evolved from a historical backdrop of disinformation campaigns, merging with the advancements of artificial intelligence (AI) and machine learning to craft convincing but false multimedia content.

Examining the capabilities of deepfakes reveals their potential for misuse, evidenced by instances targeting individuals, companies, and even influencing political events like the 2020 U.S. elections. The paper highlights the direct threats posed by …

Privacy Concerns And Proposed Solutions With Iot In Wearable Technology, Hyacinth Abad

Cybersecurity Undergraduate Research Showcase

This paper examines the dynamic relationship between IoT cybersecurity and privacy concerns associated with wearable devices. IoT, with its exponential growth, presents both opportunities and challenges in terms of accessibility, integrity, availability, scalability, confidentiality, and interoperability. Cybersecurity concerns arise as diverse attack surfaces exploit vulnerabilities in IoT systems, necessitating robust defenses. In the field of wearable technology, these devices offer benefits like health data tracking and real-time communication. However, the adoption of these devices raises privacy concerns. The paper explores proposed solutions, including mechanisms for user-controlled data collection, the implementation of Virtual Trip Line (VTL) and virtual wall approaches, and …

Robots Still Outnumber Humans In Web Archives In 2019, But Less Than In 2012, Himarsha R. Jayanetti, Kritika Garg, Sawood Alam, Michael L. Nelson, Michele C. Weigle

College of Sciences Posters

To identify robots and human users in web archives, we conducted a study using the access logs from the Internet Archive’s (IA) Wayback Machine in 2012 (IA2012), 2015 (IA2015), and 2019 (IA2019), and the Portuguese Web Archive (PT) in 2019 (PT2019). We identified user sessions in the access logs and classified them as human or robot based on their browsing behavior. In 2013, AlNoamany et al. [1] studied the user access patterns using IA access logs from 2012. They established four web archive user access patterns: single-page access (Dip), access to the same page at multiple archive times (Dive), access …

Adhd Prediction Through Analysis Of Eye Movements With Graph Convolution Network, Gavindya Jayawardena, Sampath Jayarathna, Yi He

College of Sciences Posters

Processing speech with background noise requires appropriate parsing of the distorted auditory signal, fundamental language abilities as well as higher signal-to-noise ratio. Adolescents with ADHD have difficulty processing speech with background noise due to reduced inhibitory control and working memory capacity. In this study we utilize Audiovisual Speech-In-Noise performance and eye-tracking measures of young adults with ADHD compared to age-matched controls, and generate graphs for ADHD evaluation using the eye-tracking data. We form graphs utilizing the eight eye-tracking features (fixation count, average, total, and standard deviation of fixation duration, max and min saccade peak velocity, min, average, and standard deviation …

A Novel Parking Management In Smart City Vehicular Datacenters, Syed Rizvi, Susan Zehra, Steven Olariu

College of Sciences Posters

Researchers have shown that most vehicles spend the majority of their time parked in parking garages, lots, or driveways. During this time, their computing resources are unused and untapped. This has led to substantial interest in Vehicular Cloud, an area of research in which each vehicle acts as a computation node. The main difference between traditional cloud computing and vehicular cloud computing is the availability of nodes. In traditional clouds, nodes are available 24/7, while in vehicular clouds, nodes (vehicles) are only available while parked in parking lots. This creates a dynamic environment as vehicles enter and exit parking garages …

Scalable Quantum Edge Detection Method For D-Nisq Imaging Simulations: Use Cases From Nuclear Physics And Medical Image Computing, Emmanuel Billias, Nikos Chrisochoides

The Graduate School Posters

Edge Detection is one of the computationally intensive modules in image analysis. It is used to find important landmarks by identifying a significant change (or “edge”) between pixels and voxels. We present a hybrid Quantum Edge Detection method by improving three aspects of an existing widely referenced implementation, which for our use cases generates incomprehensible results for the type and size of images we are required to process. Our contributions are in the pre- and post-processing (i.e., classical phase) and a quantum edge detection circuit: (1) we use space- filling curves to eliminate image artifacts introduced by the image decomposition, …

Metaenhance: Metadata Quality Improvement For Electronic Theses And Dissertations, Muntabir H. Choudhury, Lamia Salsabil, Himarsha R. Jayanetti, Jian Wu

College of Sciences Posters

Metadata quality is crucial for digital objects to be discovered through digital library interfaces. Although DL systems have adopted Dublin Core to standardize metadata formats (e.g., ETD-MS v1.1¹), the metadata of digital objects may contain incomplete, inconsistent, and incorrect values [1]. Most existing frameworks to improve metadata quality rely on crowdsourced correction approaches, e.g., [2]. Such methods are usually slow and biased toward documents that are more discoverable by users. Artificial intelligence (AI) based methods can be adopted to overcome this limit by automatically detecting, correcting, and canonicalizing the metadata, featuring quick and unbiased responses to document metadata. …

X-Disetrac: Distributed Eye-Tracking With Extended Realities, Bhanuka Mahanama, Sampath Jayarathna

College of Sciences Posters

Humans use heterogeneous collaboration mediums such as in-person, online, and extended realities for day-to-day activities. Identifying patterns in viewpoints and pupillary responses (a.k.a eye-tracking data) provide informative cues on individual and collective behavior during collaborative tasks. Despite the increasing ubiquity of these different mediums, the aggregation and analysis of eye-tracking data in heterogeneous collaborative environments remain unexplored. Our study proposes X-DisETrac: Extended Distributed Eye Tracking, a versatile framework for eye tracking in heterogeneous environments. Our approach tackles the complexity by establishing a platform-agnostic communication protocol encompassing three data streams to simplify data aggregation and …

Covid-19 Crowd Detection, Mustafa Ibrahim, Aly M. Zeineldin, Yameen Khan, Ayman Elmesalami, Soad Ibrahim

OUR Journal: ODU Undergraduate Research Journal

Object detection was introduced by researchers for face detection. Researchers explain how the detected face is divided into minor frames to be recognized by the algorithm. Due to COVID-19 and government regulations, many people face problems going to shopping centers and shop safely. It has been very hard for both the government and the people to manage social distancing. In our study, we developed a system using Raspberry Pi-4 that will detect the distance between people along with counting the number of distance and mask violations. An error message will appear on the screen in red, showing the total number …

Murder On The Vr Express: Studying The Impact Of Thought Experiments At A Distance In Virtual Reality, Andrew Kissel, Krzysztof J. Rechowicz, John B. Shull

Philosophy Faculty Publications

Hypothetical thought experiments allow researchers to gain insights into widespread moral intuitions and provide opportunities for individuals to explore their moral commitments. Previous thought experiment studies in virtual reality (VR) required participants to come to an on-site laboratory, which possibly restricted the study population, introduced an observer effect, and made internal reflection on the participants’ part more difficult. These shortcomings are particularly crucial today, as results from such studies are increasingly impacting the development of artificial intelligence systems, self-driving cars, and other technologies. This paper explores the viability of deploying thought experiments in commercially available in-home VR headsets. We conducted …

The Message Design Of Raiders Of The Lost Ark On The Atari 2600 & A Fan’S Map, Quick Start, And Strategy Guide, Miguel Ramlatchan, William I. Ramlatchan

Distance Learning Faculty & Staff Books

The message design and human performance technology in video games, especially early video games have always been fascinating to me. From an instructional design perspective, the capabilities of the technology of the classic game consoles required a careful balance of achievable objectives, cognitive task analysis, guided problem solving, and message design. Raiders on the Atari is an excellent example of this balance. It is an epic adventure game, spanning 13+ distinct areas, with an inventory of items, where those hard to find items had to be used by the player to solve problems during their quest (and who would have …

Analysis Of An Existing Method In Refinement Of Protein Structure Predictions Using Cryo-Em Images, Maytha Alshammari, Jing He, Willy Wriggers, Jiangwen Sun

College of Sciences Posters

Protein structure prediction produces atomic models from its amino acid sequence. Three-dimensional structures are important for understanding the function mechanism of proteins. Knowing the structure of a given protein is crucial in drug development design of novel enzymes. AlphaFold2 is a protein structure prediction tool with good performance in recent CASP competitions. Phenix is a tool for determination of a protein structure from a high-resolution 3D molecular image. Recent development of Phenix shows that it is capable to refine predicted models from AlphaFold2, specifically the poorly predicted regions, by incorporating information from the 3D image of the protein. The goal …

Diabetic Foot Exam System, Stephanie Trusty

Undergraduate Research Symposium

The diabetic foot exam system aims to perform certain aspects of the dermatological and musculoskeletal assessments that are typical to a 3-minute diabetic foot exam. Utilizing the RaspberryPi computer and camera module, the system seeks to capture a series of images of the patient’s foot. It then evaluates these images for calluses, blisters, and three types of deformities: claw toe deformities, hammertoe deformities, and bunions. This evaluation is performed using a trained TensorFlow image classification model, which categorizes the image as a callus, blister, or deformity. The system was tested using six different images: four callus images, a hammertoe deformity …

Covid-19 Classroom Occupancy Detection System, Stephanie Trusty

Undergraduate Research Symposium

The classroom occupancy detection system aims to limit the spread of COVID-19 and support mitigation efforts advised by national and international health organizations by enforcing social distancing in classroom environments. Utilizing the RaspberryPi computer and its compatible camera module, the system accomplishes this by capturing an overhead image of a classroom and assessing the image for violations. Here, violations are defined as the presence of adjacent occupied seats. As such, for an acceptable state to be detected, there must be at least one vacant seat between all students seated in the classroom. The system communicates the classroom’s state with two …

Odu Undergraduate Students Addressing The Societal Problems Of Parking Control, Classroom Seating, And Flood Monitoring In Hampton Roads, Stephanie K. Trusty, Gabriel Del Razo, Nathan Potter, Soad Ibrahim, Ayman Elmesalami

OUR Journal: ODU Undergraduate Research Journal

During the summer of 2021, ODU undergraduate computer science students undertook image processing research projects. These projects focused on utilizing the Raspberry Pi computer and camera module to address three real-world problems concerning parking control, classroom seating, and flood monitoring. The parking lot occupancy project aimed to develop a system that monitors the occupancy of parking spaces in a lot and communicates the status of the lot of drivers and the lot attendants. The COVID-19 classroom occupancy project sought to enforce social distancing protocols in a classroom environment by detecting seating violations and notifying the instructor and the impacted students …

Multiplicative Noise Removal: Nonlocal Low-Rank Model And It's Proximal Alternating Reweighted Minimization Algorithm, Xiaoxia Liu, Jian Lu, Lixin Shen, Chen Xu, Yuesheng Xu

Mathematics & Statistics Faculty Publications

The goal of this paper is to develop a novel numerical method for efficient multiplicative noise removal. The nonlocal self-similarity of natural images implies that the matrices formed by their nonlocal similar patches are low-rank. By exploiting this low-rank prior with application to multiplicative noise removal, we propose a nonlocal low-rank model for this task and develop a proximal alternating reweighted minimization (PARM) algorithm to solve the optimization problem resulting from the model. Specifically, we utilize a generalized nonconvex surrogate of the rank function to regularize the patch matrices and develop a new nonlocal low-rank model, which is a nonconvex …