Computer Sciences Commons^™

Analysis Of Gpu Memory Vulnerabilities, Jarrett Hoover

Computer Science and Computer Engineering Undergraduate Honors Theses

Graphics processing units (GPUs) have become a widely used technology for various purposes. While their intended use is accelerating graphics rendering, their parallel computing capabilities have expanded their use into other areas. They are used in computer gaming, deep learning for artificial intelligence and mining cryptocurrencies. Their rise in popularity led to research involving several security aspects, including this paper’s focus, memory vulnerabilities. Research documented many vulnerabilities, including GPUs not implementing address space layout randomization, not zeroing out memory after deallocation, and not initializing newly allocated memory. These vulnerabilities can lead to a victim’s sensitive data being leaked to an …

Using A Bert-Based Ensemble Network For Abusive Language Detection, Noah Ballinger

Computer Science and Computer Engineering Undergraduate Honors Theses

Over the past two decades, online discussion has skyrocketed in scope and scale. However, so has the amount of toxicity and offensive posts on social media and other discussion sites. Despite this rise in prevalence, the ability to automatically moderate online discussion platforms has seen minimal development. Recently, though, as the capabilities of artificial intelligence (AI) continue to improve, the potential of AI-based detection of harmful internet content has become a real possibility. In the past couple years, there has been a surge in performance on tasks in the field of natural language processing, mainly due to the development of …

Canary: An Automated Approach To Security Scanning And Remediation, David Wiles

Masters Theses & Specialist Projects

Modern software has a smaller attack surface today than in the past. Memory-safe languages, container runtimes, virtual machines, and a mature web stack all contribute to the relative safety of the web and software in general compared to years ago. Despite this, we still see high-profile bugs, hacks, and outages which affect major companies and widely-used technologies. The extensive work that has gone into hardening virtualization, containerization, and commonly used applications such as Nginx still depends on the end-user to configure correctly to prevent a compromised machine.

In this paper, I introduce a tool, which I call Canary, which can …

The Primitive Root Problem: A Problem In Bqp, Shixin Wu

Mathematical Sciences Technical Reports (MSTR)

Shor’s algorithm proves that the discrete logarithm problem is in BQP. Based on his algorithm, we prove that the primitive root problem, a problem that verifies if some integer g is a primitive root modulo p where p is the largest prime number smaller than 2n for a given n, which is assumed to be harder than the discrete logarithm problem, is in BQP by using an oracle quantum Turing machine.

Side-Channel Analysis On Post-Quantum Cryptography Algorithms, Tristen Teague

Computer Science and Computer Engineering Undergraduate Honors Theses

The advancements of quantum computers brings us closer to the threat of our current asymmetric cryptography algorithms being broken by Shor's Algorithm. NIST proposed a standardization effort in creating a new class of asymmetric cryptography named Post-Quantum Cryptography (PQC). These new algorithms will be resistant against both classical computers and sufficiently powerful quantum computers. Although the new algorithms seem mathematically secure, they can possibly be broken by a class of attacks known as side-channels attacks (SCA). Side-channel attacks involve exploiting the hardware that the algorithm runs on to figure out secret values that could break the security of the system. …

Ransomware And Malware Sandboxing, Byron Denham

Computer Science and Computer Engineering Undergraduate Honors Theses

The threat of ransomware that encrypts data on a device and asks for payment to decrypt the data affects individual users, businesses, and vital systems including healthcare. This threat has become increasingly more prevalent in the past few years. To understand ransomware through malware analysis, care must be taken to sandbox the ransomware in an environment that allows for a detailed and comprehensive analysis while also preventing it from being able to further spread. Modern malware often takes measures to detect whether it has been placed into an analysis environment to prevent examination. In this work, several notable pieces of …

A Study Of Software Development Methodologies, Kendra Risener

Computer Science and Computer Engineering Undergraduate Honors Theses

Software development methodologies are often overlooked by software engineers as aspects of development that are handled by project managers alone. However, if every member of the team better understood the development methodology being used, it increases the likelihood that the method is properly implemented and ultimately used to complete the project more efficiently. Thus, this paper seeks to explore six common methodologies: the Waterfall Model, the Spiral Model, Agile, Scrum, Kanban, and Extreme Programming. These are discussed in two main sections in the paper. In the first section, the frameworks are isolated and viewed by themselves. The histories, unique features, …

Comparative Study Of Snort 3 And Suricata Intrusion Detection Systems, Cole Hoover

Computer Science and Computer Engineering Undergraduate Honors Theses

Network Intrusion Detection Systems (NIDS) are one layer of defense that can be used to protect a network from cyber-attacks. They monitor a network for any malicious activity and send alerts if suspicious traffic is detected. Two of the most common open-source NIDS are Snort and Suricata. Snort was first released in 1999 and became the industry standard. The one major drawback of Snort has been its single-threaded architecture. Because of this, Suricata was released in 2009 and uses a multithreaded architecture. Snort released Snort 3 last year with major improvements from earlier versions, including implementing a new multithreaded architecture …

Using Bluetooth Low Energy And E-Ink Displays For Inventory Tracking, David Whelan

Computer Science and Computer Engineering Undergraduate Honors Theses

The combination of Bluetooth Low energy and E-Ink displays allow for a low energy wire-less display. The application of this technology is far reaching especially given how the Bluetooth Low Energy specification can be extended. This paper proposes an extension to this specification specifically for inventory tracking. This extension combined with the low energy E-Ink display results in a smart label that can keep track of additional meta data and inventory counts for physical inventory. This label helps track the physical inventory and can help mitigate any errors in the logical organization of inventory.

Data And Algorithmic Modeling Approaches To Count Data, Andraya Hack

Honors College Theses

Various techniques are used to create predictions based on count data. This type of data takes the form of a non-negative integers such as the number of claims an insurance policy holder may make. These predictions can allow people to prepare for likely outcomes. Thus, it is important to know how accurate the predictions are. Traditional statistical approaches for predicting count data include Poisson regression as well as negative binomial regression. Both methods also have a zero-inflated version that can be used when the data has an overabundance of zeros. Another procedure is to use computer algorithms, also known as …

Development Of Classroom Tools For A Risc-V Embedded System, Lucas Phillips

Undergraduate Honors Theses

RISC-V is an open-source instruction set that has been gaining popularity in recent years, and, with support from large chip manufacturers like Intel and the benefits of its open-source nature, RISC-V devices are likely to continue gaining momentum. Many courses in a computer science program involve development on an embedded device. Usually, this device is of the ARM architecture, like a Raspberry Pi. With the increasing use of RISC-V, it may be beneficial to use a RISC-V embedded device in one of these classroom environments. This research intends to assist development on the SiFive HiFive1 RevB, which is a RISC-V …

Simulating Polistes Dominulus Nest-Building Heuristics With Deterministic And Markovian Properties, Benjamin Pottinger

Undergraduate Honors Theses

European Paper Wasps (Polistes dominula) are social insects that build round, symmetrical nests. Current models indicate that these wasps develop colonies by following simple heuristics based on nest stimuli. Computer simulations can model wasp behavior to imitate natural nest building. This research investigated various building heuristics through a novel Markov-based simulation. The simulation used a hexagonal grid to build cells based on the building rule supplied to the agent. Nest data was compared with natural data and through visual inspection. Larger nests were found to be less compact for the rules simulated.

Inter-Cell Slicing Resource Partitioning Via Coordinated Multi-Agent Deep Reinforcement Learning, Tianlun Hu, Qi Liao, Qiang Liu, Dan Wellington, Georg Carle

School of Computing: Faculty Publications

Network slicing enables the operator to configure virtual network instances for diverse services with specific requirements. To achieve the slice-aware radio resource scheduling, dynamic slicing resource partitioning is needed to orchestrate multi-cell slice resources and mitigate inter-cell interference. It is, however, challenging to derive the analytical solutions due to the complex inter-cell interdependencies, interslice resource constraints, and service-specific requirements. In this paper, we propose a multi-agent deep reinforcement learning (DRL) approach that improves the max-min slice performance while maintaining the constraints of resource capacity. We design two coordination schemes to allow distributed agents to coordinate and mitigate inter-cell interference. The …

What About Generic "And"- And "Or"-Operations: From Levels Of Certainty (Philosophical-Physical-Mathematical) To A Natural Interpretation Of Quantum-Like Negative Degrees Of Certainty, Miroslav Svitek, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Fuzzy techniques -- techniques designed to convert imprecise human knowledge into precise computer-understandable terms -- have many successful applications. Traditional applications of fuzzy techniques use only important general features of human reasoning and, to make an implement more efficient, ignore subtle details, details which are not important for the corresponding application. But from the more fundamental viewpoint, it is desirable to understand, in all the detail, how people actually reason. In this paper, we use general ideas of fuzzy approach to answer this question. Interestingly -- and somewhat unexpectedly -- the resulting analysis leads to a natural explanation of existence …

How Can The Opposite To A True Theory Be Also True? A Similar Talmudic Discussion Helps Make This Famous Bohr's Statement Logically Consistent, Miroslav Svitek, Vladik Kreinovich

Departmental Technical Reports (CS)

In his famous saying, the Nobelist physicist Niels Bohr claimed that the sign of a deep theory is that while this theory is true, its opposite is also true. While this statement makes heuristic sense, it does not seem to make sense from a logical viewpoint, since, in logic, the opposite to true is false. In this paper, we show how a similar Talmudic discussion can help come up with an interpretation in which Bohr's statement becomes logically consistent.

In The Absence Of Information, The Only Reasonable Negotiation Scheme Is Offering A Certain Percentage Of The Original Request: A Proof, Miroslav Svitek, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In the case of complete information, a reasonable solution to a negotiation process is Nash's bargaining solution, in which we maximize the product of all agents' utility gains. This is the only solution that does not depend on the order in which we list the agents, and does not change if we use a different scale for describing each agent's utility. In this paper, we apply similar invariance criteria to a situation when practically all information is absent, and all we know is the smallest and largest possible gains. We show that in this situation, the only invariant negotiation strategy …

Why Some Theoretically Possible Representations Of Natural Numbers Were Historically Used And Some Were Not: An Algorithm-Based Explanation, Christian Servin, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Historically, people have used many ways to represent natural numbers: from the original "unary" arithmetic, where each number is represented as a sequence of, e.g., cuts (4 is IIII) to modern decimal and binary systems. However, with all this variety, some seemingly reasonable ways of representing natural numbers were never used. For example, it may seem reasonable to represent numbers as products -- e.g., as products of prime numbers -- such a representation was never used in history. So why some theoretically possible representations of natural numbers were historically used and some were not? In this paper, we propose an …

Stumbling Into Virtual Worlds. How Resolution Affects Users’ Immersion In Virtual Reality And Implications For Virtual Reality In Therapeutic Applications, Brianna Martinson

Undergraduate Honors Theses

Studies of how users experience Virtual Reality (VR) have thus far failed to address the extent to which rendering resolution and rendering frame rate affect users’ sense of immersion in VR, including applications of VR involving simulators, treatments for psychological and mental disorders, explorations of new and nonexistent structures, and ways to better understand the human body in medical applications.

This study investigated if rendering resolution affected users’ sense of immersion in VR. This was conducted by comparing the responses of two groups, relative to two measures of participant immersion: (a) participant’s sense of presence and (b) participant’s sense of …

Intraday Algorithmic Trading Using Momentum And Long Short-Term Memory Network Strategies, Andrew R. Whitinger Ii

Undergraduate Honors Theses

Intraday stock trading is an infamously difficult and risky strategy. Momentum and reversal strategies and long short-term memory (LSTM) neural networks have been shown to be effective for selecting stocks to buy and sell over time periods of multiple days. To explore whether these strategies can be effective for intraday trading, their implementations were simulated using intraday price data for stocks in the S&P 500 index, collected at 1-second intervals between February 11, 2021 and March 9, 2021 inclusive. The study tested 160 variations of momentum and reversal strategies for profitability in long, short, and market-neutral portfolios, totaling 480 portfolios. …

Human Behavior Modeling In Long Videos: Drowsiness Detection And Action Segmentation, Reza Ghoddoosian

Computer Science and Engineering Dissertations - Archive

"In this thesis we focus on two instances of human behavior modeling in long untrimmed videos: drowsiness detection, and action segmentation. In the first section, we focus on drowsiness detection. Specifically, we introduce a large and public real-life dataset and a baseline temporal model to classify drowsiness into three stages of alert, low vigilant, or drowsy. In the second section, we study action segmentation in instructional videos under weak supervision. In order to save time and cost, weakly supervised methods are trained based on only video-level action sequences as opposed to a fully supervised method which is trained using frame-level …

Learning Topology Preserving Embeddings For Speeding Up Nearest Neighbor Retrieval, Mason Lary

Computer Science and Engineering Theses - Archive

Given a database of objects and a query object, it’s possible to gather a number of the closest neighbors to the query object. This operation is important to a number of diverse fields such as computer vision, content- based information retrieval, and chemistry. However, distance measures used to determine neighbors can cause queries to be computationally expensive, either because the distance measure is complex or because it is nonmetric and prevents efficient indexing methods. This work presents novel methods of triplet mining that enable neural networks using triplet loss to learn the manifold that data resides in. These neural networks …

Distraction Detection And Intention Recognition For Gesture-Controlled Unmanned Aerial Vehicle Operation, Debayan Datta

Computer Science and Engineering Theses - Archive

Gesture Control as a way to replace more conventional remote-control operations has been pursued for a significant period of time with different levels of success. The use of gestures to control different types of human interfaces is today predominantly seen in the multimedia sector. People perform easy and intuitive gestures to control their televisions, to interact with multimedia, and to play games. Also, much research has been carried out to experiment with human interfaces to numerous augmented and virtual reality devices and tasks. The results of these experiments were so exciting that researchers started to expand the use of gestures …

Detection And Classification Of Object Presence And Characteristics In A Water Container Using High Frequency Ultrasound, Mehul Vishal Sadh

Computer Science and Engineering Theses - Archive

Detection and characterization of soluble, diffuse, and solid objects and their characteristics in water has important implications in various applications, including water quality assessment and incontinence monitoring for health applications. In particular in the latter task, it is essential to be able to non-intrusively detect the appearance, presence, and consistency of materials in the water without the need for special purpose instruments or a special purpose setting. Rather, it would be important that sensing could be performed int he context of existing toilet systems. To achieve this, this work investigates the potential use of high frequency sonar sensors retrofitted to …

A Combinatorial Approach To Fairness Testing Of Machine Learning Models, Ankita Ramjibhai Patel

Computer Science and Engineering Theses - Archive

Machine Learning (ML) models could exhibit biased behavior, or algorithmic discrimination, resulting in unfair or discriminatory outcomes. The bias in the ML model could emanate from various factors such as the training dataset, the choice of the ML algorithm, or the hyperparameters used to train the ML model. In addition to evaluating the model’s correctness, it is essential to test ML models for fair and unbiased behavior. In this thesis, we present a combinatorial testing-based approach to perform fairness testing of ML models. Our approach is model agnostic and evaluates fairness violations of a pre-trained ML model in a two-step …

“Strict Moderation?” The Impact Of Increased Moderation On Parler Content And User Behavior, Nihal Kumarswamy

Computer Science and Engineering Theses - Archive

Social media platforms have brought people from different backgrounds, ethnicity, race, gender, etc together to form a platform to share ideas and opinions and discuss news events among other social events. Unfortunately, these platforms have also been a safe haven for abusive users who harass, bully other users or spread misinformation and disinformation. Social media platforms have a huge incentive to police these abusive users and keep them in check to allow other genuine users to use their platform. Social media platforms employ several different content moderation techniques to perform this task. These techniques vary across platforms, for example, Parler …

A Non-Contact Based System To Measure Spo2 And Systolic/Diastolic Blood Pressure Using Rgb-Nir Camera, Divya Saxena

Computer Science and Engineering Theses - Archive

In recent times, people have increasingly self-assessed their health using different devices on their bodies that monitor physiological attributes such as their oxygen level and blood pressure (BP) to monitor their health. One of the most popular health concerns that became prominent during the COVID-19 pandemic was the blood oxygen saturation (SPO2) level. It became increasingly important to monitor SPO2 in patients, time and again to determine whether the right amount of oxygen is in the blood. Low oxygen levels usually indicate there may be an issue with oxygen circulation or supply and thus informs diagnostic and treatment decisions such …

Visualcommunity: A Platform For Archiving And Studying Communities, Suphanut Jamonnak, Deepshikha Bhati, Md Amiruzzaman, Ye Zhao, Xinyue Ye, Andrew Curtis

Computer Science Faculty Publications

VisualCommunity is a platform designed to support community or neighborhood scale research. The platform integrates mobile, AI, visualization techniques, along with tools to help domain researchers, practitioners, and students collecting and working with spatialized video and geo-narratives. These data, which provide granular spatialized imagery and associated context gained through expert commentary have previously provided value in understanding various community-scale challenges. This paper further enhances this work AI-based image processing and speech transcription tools available in VisualCommunity, allowing for the easy exploration of the acquired semantic and visual information about the area under investigation. In this paper we describe the specific …

Sl-Cyclegan: Blind Motion Deblurring In Cycles Using Sparse Learning, Ali Syed Saqlain, Li-Yun Wang, Zhiyong Liu

Computer Science Faculty Publications and Presentations

In this paper, we introduce an end-to-end generative adversarial network (GAN) based on sparse learning for single image motion deblurring, which we called SL-CycleGAN. For the first time in image motion deblurring, we propose a sparse ResNet-block as a combination of sparse convolution layers and a trainable spatial pooler k-winner based on HTM (Hierarchical Temporal Memory) to replace non-linearity such as ReLU in the ResNet-block of SL-CycleGAN generators. Furthermore, we take our inspiration from the domain-to-domain translation ability of the CycleGAN, and we show that image deblurring can be cycle-consistent while achieving the best qualitative results. Finally, we perform extensive …

Detecting The Intensity Of Denial-Of-Service Cyber Attacks Using Supervised Machine Learning, Abigail Hubbard

Undergraduate Honors Theses

Denial-of-Service (DoS) attacks are aimed at shutting a machine or network down to block users from accessing it. These attacks can be difficult to detect and can cost millions in damages or lost earnings. Since the first DoS attack occurred in 1999, the way DoS attacks have been launched has become more complicated, making them more elusive and harder to detect. The first step to detect and mitigate a DoS attack is for a system to identify the malicious traffic.

In this experiment, we aim to identify the malicious traffic within ten seconds. To do this the project was divided …

Improving Intelligent Transportation Safety And Reliability Through Lowering Costs, Integrating Machine Learning, And Studying Model Sensitivity, Cavender Holt

All Theses

As intelligent transportation becomes increasingly prevalent in the domain of transportation, it is essential to understand the safety, reliability, and performance of these systems. We investigate two primary areas in the problem domain. The first area concerns increasing the feasibility and reducing the cost of deploying pedestrian detection systems to intersections in order to increase safety. By allowing pedestrian detection to be placed in intersections, the data can be better utilized to create systems to prevent accidents from occurring. By employing a dynamic compression scheme for pedestrian detection, we show the reduction of network bandwidth improved by 2.12× over the …