Annual Research Symposium

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  Assessing Security Flaws in Modern Precision Farming Systems

  Joseph Boyd and Robert Richardson

  The increasing interconnectivity of the digital age brings new vulnerabilities for cyber criminals and nation state threat actors alike. Every day, threat actors make millions of at-tacks against a variety of systems. Though not all these attacks prove successful, they all share the same goal of manipulating or extracting data from their targets. The dawn of digitalization in the agricultural industry finds itself under the same threats. Because agriculture sits within the category of critical infrastructure, digitizing this industry should be accompanied with special concern for implementing good security practices. At a basic level, good cyber security practice includes ensuring that data remains confidential to users and processes, ensuring that data remains unmodified by unauthorized methods, and ensuring the accessibility of the data. However, no system can be made completely secure. Some form of exploitation will always exist by which proprietary data of the customer, or the manufacturer, can be leaked or abused. Thus, this paper does not ask if vulnerabilities exist on on-board precision farming equipment, but rather it asks what level of risk these exploits possess. In other words, if a vulnerability becomes exploited, what access or data does the attacker gain and does its value equal the amount of effort required to obtain it? The likely answer exposes vulnerabilities that damage the finances or reputations of individual producers and manufactures, which may provide an equal level of danger to the industry if these attacks can be scaled up against multiple targets.

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  Assessing Security Vulnerabilities in Wireless IoT Devices

  John Brumels

  This research project aims to systematically assess and analyze security vulnerabilities in accessibility technology, specifically devices related to the American Disabilities Act (ADA), such as wheelchair lifts, ADA buttons, and light switches. The project focuses on the potential risks associated with radio frequency (RF) replay attacks, a well-documented threat in IoT security. By examining the vulnerabilities and consequences of RF replay attacks in these critical areas, the research seeks to enhance the security and safety of individuals with disabilities and the broader public. The project also explores potential countermeasures and ethical considerations for responsible vulnerability disclosure, contributing to the fields of accessibility technology, IoT security, and ethical cybersecurity practices.

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  Do online test proctoring services abide by standard data protections?

  Tristan Stapert and Andrew Kramer

  In the aftermath of the COVID-19 pandemic, schools adopted new software to allow for online learning. Online exam proctoring has seen rapid growth in both K-12 and higher education. The security of these suites is critical due to their extensive access. Online proctoring suites have the capabilities to assess and configure student devices, access the microphone and cam-era, and view student information in the scope of the exam. This case study investigates the security of data sent over the network using dynamic software analysis and network monitoring while using the Respondus Lockdown Browser.

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  Exploring the Antimicrobial Potential of Honey from Alfalfa (Medicago sativa) Against Both Human and Plant Pathogens

  Denyce Bravo and Andrew Santhoff

  Alfalfa (Medicago sativa) is the third most valuable crop in the United States. It produces a large amount of nectar from which honeybees and other types of bees produce a high yield of honey. It is estimated that around 416 to 1,933 pounds of nectar per acre is produced by alfalfa (Kropacova, 1963). However, even with the great antimicrobial features that honey offers, there is still limited research on the antimicrobial properties of specific types of honey, such as alfalfa honey. Topical honey application clears wounds swiftly, aiding rapid healing, even in infections resistant to typical antibiotics like methicillin-resistant Staphylococcus aureus (MRSA). Manuka honey from tea tree in Australia and New Zealand effectively combats human pathogens including Escherichia coli, Klebsiella aerogenes, Salmonella typhimurium, and Staphylococcus aureus, as well as MRSA (Mandal et al., 2011). Alfalfa honey, among others from Saudi Arabia, exhibits high antioxidant potential and significant antimicrobial activity, ranking second only to Acacia honey (Ismail et al., 2021). Honey comprises primarily of different sugars and proteins (0.5%), with variations based on bee species and flora. Hydrogen peroxide (H2O2) is the main antimicrobial agent in honey, confirmed by spectrophoto-metric assays. Other non-peroxide antimicrobial factors include low water content, low pH, phenolic compounds, and bee defensin-1 (Def-1).

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  Micromouse - Maze Solving Robot

  Aiden Schramm, David Medin, and Andrew Kramer

  A Micromouse is a path-finding robot designed to traverse and map a maze to determine the shortest path possible. These robots are typically entered in annual Micromouse competitions to compete against other teams for achieving the best possible time in solving the maze in the most efficient manner.

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  Natural Language Processing: Understanding Slang and Colloquial Speech

  Beau Miller

  Within the field of Natural Language Processing, slang and colloquial language provide a unique challenge for the training and use of language models. This speech holds an odd, transient space with public consciousness, as each instance has a variable time of relevancy and popularity, amongst other factors such as their fluid definition, usage amongst certain groups, and relative lack of information and training data concerning new or evolving terms. These characteristics make it difficult for models to learn these phrases in a timely manner. This project focuses on how a NLP model could learn new additions to colloquial language in a timely and efficient manner, as well as keep up with a rapidly mutating lexicon.

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  Resonant Landscapes

  Tate Carson and Cater Gordon

  Immersive ambisonics field recordings of 13 South Dakota State Parks. Used for: interactive smartphone-based sound art exhibit and immersive soundscape compositions. Goal: by studying a park's soundscape through immersive recording, we can gain a deeper understanding and appreciation for its unique sonic characteristics.

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  Surveying for Ophidiomyces ophidiicola, the causal agent of Snake Fungal Disease in South Dakota.

  Adam Peak, Brandon Daniels, and Andrew E. Sathoff

  For the past decade there has been an emerging disease plaguing wild snakes across the Eastern United States and Europe. In 2006, researchers started investigating the decline of Timber rattlesnake populations in New Hampshire. They discovered a fungal infection killing off the young to mid-juvenal snakes, thus know as Snake Fungal Disease or Ophidiomycosis. In 2011, San Deigo State University, identified the pathogen that causes infection, the fungus Ophidiomyces ophiodiicola. O. ophiodiicola has now affected 30 different snakes from six families within at least 20 different states since it’s discovery. This study pertains to determining the prevalence of Snake Fungal Disease within South Dakota.

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  The Impact of Family Business Ownership and Involvement on Entrepreneurial Self-Identification

  Ephrata Yared Feyissa and Robert Girtz

  In this study I analyze the impact that family business ownership has on the tendency of individuals to identify as being entrepreneurial. Drawing data from the 1979 cohort of the National Longitudinal Survey of Youth, I use two-sample t-tests and logistic regression models to explore the relationship between personal entrepreneurial aspirations and having come from an environment involving a family business. As part of this analysis, I control for several demographic factors, such as cognition, gender, and ethnicity. The outcomes from this research highlight the importance of family business as a key factor in fostering entrepreneurial mindsets, suggesting that the experiences and cultural context provided by family-owned enterprises are instrumental in encouraging future generations of entrepreneurship.

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  Do AI-Generated Political Advertisements Create Positive or Negative Responses from Voters?

  Grace Schofield

  Artificial intelligence (AI) is advancing at breakneck speeds, and it’s more important than ever that voters understand AI’s implications on the United States’ political landscape. Political campaigns can synthesize political advertisements using genera-tive AI, fabricating images and videos alike. The public often has difficulty distinguishing these advertisements from their genuine, non-AI counterparts—and deepfake technology improves exponentially, causing the public to struggle even more in identifying AI-generated advertisements.

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  Feature Extraction and Analysis of Binaries for Classification

  Micah Flack

  The research project, Feature Extraction and, Analysis of Binaries for Classification, provides an in-depth examination of the features shared by unlabeled binary samples, for classification into the categories of benign or malicious software using several different methods. Because of the time it takes to manually analyze or reverse engineer binaries to determine their function, the ability to gather features and then instantly classify samples without explicitly programming the solution is incredibly valuable. It is possible to use an online service; however, this is not always viable depending on the sensitivity of the binary. With Python3 and the Pefile library, we can gather the necessary features to begin choosing different classifier models from the Scikit-learn library for machine learning. This all addresses the issue of local automated classification, and we present several different classifier models, datasets and methods that allow for the classification of unknown binaries with a high degree of accuracy for predicting malware and benignware.

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  Accessing the Impact of IT Budgets on Hospital Performance: A Panel Data Analysis

  Giridhar Reddy Bojja, and Jun Liu

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  A Stream of Consciousness

  Truman Weyand

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  Bust-A-Binary: Active Attribution and Analysis of Malware Campaigns

  Micah Flack, Nathan Kramer, Zayn Snyder, Ezra Chona, Matthew Steckelberg, and Bramwell Brizendine

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  Comparison of 2 Alternative Systems for Measuring Vertical Jump Height

  Mariah Fixen and Scott Staiger

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  Computer Modelling of Projectile Trajectory through Fluid

  Samuel Drummond

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  Creatures Of Yarn

  Gareth Brewer

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  Detecting and Mitigating Cyberattacks Targeting Healthcare Transactions

  Robert Cannistra, Josh Stroschein, and Yong Wang

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  EFFECTIVENESS OF TRANSFER LEARNING ON MEDICAL IMAGE CLASSIFICATION USING CHEST-XRAY 14 DATASET

  James Boit and David Zeng

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  Employee Acceptance of Employer Control over BYOD Devices

  Kevin Callies and Cherie Noteboom

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  Factors influencing curriculum adoption in undergraduate cybersecurity programs

  Todd Whittaker and Cherie Noteboom

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  How Does the Visualization of Data Change how it is Interpreted?

  Alexis VanderWilt and Cherie Noteboom

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  Impact of Backward Design on 4th Grade Mathematics Students’ Understanding of Adding and Subtracting Whole Numbers

  Andrew Fiegen and Kindra Schneider

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  Impact of Social Networks on the Spread of Disease

  Alexis VanderWilt, Mark Spanier, and Jeffrey S. Palmer

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  INCORPORATING SEQUENTIAL FEATURE MAPS FEEDING INTO MULTIPLE PATHS

  Rajesh Godasu, David Zeng, James Boit, and Seema Bhandari