Digital Commons Network^™

Implementing Selective Signature Scanning To Optimize Malware Detection, Lucas Gray Wilbur

Computer Science Senior Theses

Signature scanning is one of the oldest types of malware detection, and it remains an essential lightweight detection method for many antivirus programs. However, signature scanning has unavoidable limitations, including an inevitably increasing runtime as malware signature databases continually expand. In this paper, we discuss the current state of signature scanning, including usage of the open-source signature scanning tool YARA. We test Zemlyanaya et al’s assertion that scanning only the beginning and end of files can reduce the runtime cost of signature database expansion — while maintaining a high level of accuracy — and find it inaccurate in the case …

Evading Antivirus Detection By Abusing File Type Identification, Chavin Udomwongsa

Computer Science Senior Theses

File type identification is a vital step in automated file processing, especially in the realm of malware detection. The challenges with file type identification and evasion techniques that take advantage of them were pointed out over a decade ago. We show that this remains the case: file type identification implementations are still fragile, especially for files with ambiguous file types. We present a novel antivirus bypass technique via crafted tar archives that evades all detection from VirusTotal and numerous antiviruses: BitDefender, F-Secure, Kaspersky, Panda Dome, Trend Micro, Quick Heal, IKARUS, Avira. These crafted files evade detection by tricking file type …

Curating Familiarity Within The Unfamiliar: Exploring Non-Native Mobile App Experiences To Create Cross-Cultural Design Frameworks, Hanna Hong

Computer Science Senior Theses

Global mobility and markets are expanding, and as a result, countries are becoming less and less monocultural. With multiple cultural affinity groups to cater towards, companies often will deploy different versions of a website or app based on the country a user is accessing it from. This strategy of catering to geographic location results in a lack of accommodation for people living within a culture that is different from their native one. In order to increase accessibility and equal ease-of-use for all audiences, designers should understand and work towards the needs of a multicultural user base. This study investigates how …

Experimental Methods In Predicting Market Drift And Other Portfolio Optimization Factors Using Graph Theory, Perry Harrison Zhang

Computer Science Senior Theses

No abstract provided.

Shader-Based Real-Time Image Tracking For Mobile Augmented Reality, Andrew Wang Chen

Computer Science Senior Theses

Image target tracking is a technique widely used in a variety of augmented reality (AR) applications to trigger AR interaction and accurately locate virtual objects relative to physical space. This project is a Unity image tracking pipeline based on the ORB feature detection and description technique that seeks to be robust enough to track images despite partial occlusion, uneven lighting, and image target depth. This pipeline employs compute shader code to conduct image tracking computations on the GPU to track images in real-time for mobile AR apps.

Impact Of Similarities In Gender And Physical Appearance Between User And Embodied Conversational Agents On Trustworthiness, Empathy, And Service Evaluation, Sookyoung Park

Dartmouth College Master’s Theses

Embodied conversational agents (ECAs) have significantly enhanced human-machine interactions and show considerable potential in various industries such as customer service, education, healthcare, entertainment, and finance [1, 2]. This study explores the impact of similarities in gender and physical appearance between ECAs and users on the perceptions of trustworthiness, empathy, and service evaluation within the context of counselor ECAs. We conducted a within-subject experiment (n=50), using a 2x2 factorial arrangement, that varied the gender and the physical appearance of four distinct AI avatars. Participants interacted with each avatar, completing a post-experiment survey and participating in semi-structured interviews. Our findings indicate that …

College Course Assignment: Maximality, Fairness, Scheduling, Emily Y. Gao

Computer Science Senior Theses

Course selection processes in universities are crucial for shaping students’ academic experiences. At Dartmouth College, undergraduates participate in a structured course selection process each term, governed by specific constraints and priorities. This thesis examines the optimization of course assignment algorithms within Dartmouth’s environment to enhance student satisfaction and maximize course enrollment. An initial investigation reveals that Dartmouth’s registrar effectively fills course seats but identifies areas for improving student satisfaction. Hypothetical scenarios beyond Dartmouth’s framework, such as indistinct priorities and excess course selections, are also explored, proposing efficient solutions with polynomial time complexity.

This thesis emphasizes fairness in the optimization process, …

Measuring Confidentiality With Multiple Observables, John J. Utley

Computer Science Senior Theses

Measuring the confidentiality of programs that need to interact with the outside world can prevent leakages and is important to protect against dangerous attacks. However, information propagation is difficult to follow through a large program with implicit information flow, tricky loops, and complicated instructions. Previous works have tackled this problem in several ways but often measure leakage a program has on average rather than the leakage produced by a set of particularly compromising interactions. We introduce new methods that target a specific set of observables revealed throughout execution to cut down on the resources needed for analysis. Our implementation examines …

Exploring Applications Of Ai In Developer-Side Web Accessibility Practices, Maria H. Cristoforo

Computer Science Senior Theses

No abstract provided.

Welfare Maximization In The Airplane Problem, Alina Chadwick

Computer Science Senior Theses

Given a set of passengers and a set of airplane seats, the goal of the airplane problem is to sit passengers in seats in a way that maximizes the sum of their total welfare, that is, the total happiness of the passengers in the plane. We aim to maximize their welfare subject to three constraints and how much they care about each constraint being satisfied: a group constraint (where passengers may want to sit together), a constraint on where in a row passengers want to sit (i.e. a window seat, a middle seat, or an aisle seat), and finally a …

Math, Chatgpt, And You: The Problem With Mathematical Accuracy In Large Language Models, Alexandre M. Hamel

Computer Science Senior Theses

ChatGPT and other Large Language Models (LLMs) currently do a good job at generating novel text across many domains, but math remains a consistent issue when it comes to the accuracy of answers generated by these models. My research into various ways to manipulate the model have led me to the conclusion that a general closed form solution to help LLMs with math is both unrealistic and likely impossible. LLMs can be trained more successfully as you narrow the problem space, but consideration must be taken on the part of human user to recognize when an LLM is detrimental to …

Connection-Saving Gate Assignment: A Computational Approach, Rob Mailley

Computer Science Senior Theses

The growth of the commercial aviation industry has yielded many interesting problems in the field of Operations Research, many of which are now able to be solved as both technology and mathematical optimization improve. A particularly interesting problem in airport operations re- search is the Aircraft Gate Assignment Problem (AGAP), which seeks to create a feasible match- ing between planes and flights at an airport. This problem is well-suited to modeling with Integer Programming, and has attracted research since the 1970s. Researchers of the AGAP have considered many different objectives, ranging from airline-focused objectives to more passenger-focused objective functions. In …

Investigating Bias In Mortgage-Rate Machine Learning Models, Will Kalikman

Computer Science Senior Theses

Banks and fintech lenders increasingly rely on computer-aided models in lending decisions. Traditional models were interpretable: decisions were based on observable factors, such as whether a borrower's credit score was above a threshold value, and explainable in terms of combinations of these factors. In contrast, modern machine learning models are opaque and non-interpretable. Their opaqueness and reliance on historical data that is the artifact of past racial discrimination means these new models risk embedding and exacerbating such discrimination, even if lenders do not intend to discriminate. We calibrate two random forest classifiers using publicly available HMDA loan data and publicly …

Open Source Supply Chain Security: A Cost-Benefit Analysis Of Achieving Various Security Thresholds In Build Environments, Carly Retterer

Computer Science Senior Theses

Open source software has become a cornerstone of modern software development, offering unparalleled opportunities for innovation and collaboration. However, its widespread adoption has also introduced a host of security vulnerabilities, particularly in the software supply chain. This paper provides a comprehensive cost-benefit analysis of achieving various security thresholds to harden the build environment, focusing on isolated, hermetic, reproducible, and bootstrappable builds. For each build type, we provide a clear definition and outline the steps required for implementation. We then evaluate the associated costs and benefits of each build, emphasizing their roles in strengthening the build environment and enhancing supply chain …

Space Bounds For Estimating Minimum Norm Of Solutions In Underconstrained Systems, Jeffrey Jiang

Computer Science Senior Theses

In this work, we wish to investigate the following situation: suppose we are in an underconstrained linear system where observations are constant but predictors are streaming in. That is, the number of predictors—and therefore the dimensionality of our solution—is changing. How hard is it for a streaming algorithm to maintain the ”size” or norm of the solution if we are constrained in space? More informally, can we keep track of the norm of the solution as new data is streaming in without naively memorizing all data and computing the solution directly? We first show a lower bound that any streaming …

Data-Driven Computing Methods For Nonlinear Physics Systems With Geometric Constraints, Yunjin Tong

Computer Science Senior Theses

In a landscape where scientific discovery is increasingly driven by data, the integration of machine learning (ML) with traditional scientific methodologies has emerged as a transformative approach. This paper introduces a novel, data-driven framework that synergizes physics-based priors with advanced ML techniques to address the computational and practical limitations inherent in first-principle-based methods and brute-force machine learning methods. Our framework showcases four algorithms, each embedding a specific physics-based prior tailored to a particular class of nonlinear systems, including separable and nonseparable Hamiltonian systems, hyperbolic partial differential equations, and incompressible fluid dynamics. The intrinsic incorporation of physical laws preserves the system's …

Ripl: Recursive Inference For Policy Learning, Kunal Jha, Jeremy R. Manning, Alberto Quattrini Li

Computer Science Senior Theses

Humans excel at understanding the thoughts and intentions of others (theory of mind) and leverage this ability to learn and adapt in social environments. However, replicating this capability in artificial agents remains a challenge. This paper explores the gap between fast, efficient learning often achieved by Reinforcement Learning (RL) algorithms and the interpretability and adaptability desired in agents interacting with humans. We propose a novel approach that integrates an inference network within existing RL frameworks. This allows agents to reason about the beliefs of others (nested reasoning) while learning optimal actions. Our method leverages approximate solutions to the I-POMDP framework, …

Examining Differences In Concept Representation Across Similarity Spaces Between Humans And Large Language Models, Krishnachandra Nair

Computer Science Senior Theses

The replication of human concept representation is a critical task for the pursuit of artificial general intelligence. With the recent influx of large language models that demonstrate text-generation capabilities nearly on par with humans, the question stands on whether these large language models can capture concepts within language. We examine this question by exploring differences in concept representation across similarity spaces between humans and LLMs. We find that, while concept representation within LLMs does partially mimic human concept representation, LLMs are greatly limited by their dependence on semantic information and cannot therefore develop an understanding of human social code or …

Embodied Visions: Interactive Installations That Reimagine Bodily Presence In Digital Imaging Apparatuses As Shadows, Yunzi Shi

Dartmouth College Master’s Theses

Contextualized within a history of technological development, the evolution of imaging devices and technologies is accompanied by the abstraction of spatial relationships between the body of the observer, the apparatus, and physical reality, which leads to disembodying experiences for the observing subject. Compared with devices and interactive experiences, critical reflection on the epistemological impact of digital imaging devices has less priority in computational imaging and human-computer interaction research. Taking an artistic approach, this thesis describes Embodied Visions, an exhibition featuring three interactive installations exploring the technical infrastructure for imaging and reflecting on the (dis)embodied experiences in the digital age. …

Latent Auto-Recursive Composition Engine: A Generative System For Creative Expression In Human-Ai Collaboration, Yenkai Huang

Computer Science Senior Theses

This thesis investigates the shifting boundaries of art in the era of Generative AI, crit-
ically examining the essence of art and the legitimacy of AI-generated works. Despite
significant advancements in the quality and accessibility of art through generative
AI, such creations frequently encounter skepticism regarding their status as authentic
art. To address this skepticism, the study explores the role of creative agency in var-
ious generative AI workflows and introduces an ”artist-in-the-loop” system tailored
for image generation models like Stable Diffusion. This system aims to deepen the
artist’s engagement and understanding of the creative process. Additionally, a novel
tool, …

Simulating Cross-Scale Solid-Fluid Interaction Phenomena, Jinyuan Liu

Dartmouth College Ph.D Dissertations

Solid-fluid interactions are ubiquitous in nature, and accurate simulation methods are essential for realistic animation, industrial design, and engineering analysis. Com- pared to large-scale coupling phenomena, simulating fine-scale interactions poses extra challenges due to factors such as surface tension, material wettability, and geometric complexity. In this thesis, we pursue novel methodologies to accurately model in- terfacial dynamics between surface-tension fluids and codimensional solids, involving capillary interactions, controllable wettability, and robust contact behaviors. Our ini- tial approach involves developing a novel three-way coupling method, which utilizes a thin liquid membrane, modelled as a simplicial mesh, to facilitate accurate momen- tum transfer, …

Toward The Integration Of Behavioral Sensing And Artificial Intelligence, Subigya K. Nepal

Dartmouth College Ph.D Dissertations

The integration of behavioral sensing and Artificial Intelligence (AI) has increasingly proven invaluable across various domains, offering profound insights into human behavior, enhancing mental health monitoring, and optimizing workplace productivity. This thesis presents five pivotal studies that employ smartphone, wearable, and laptop-based sensing to explore and push the boundaries of what these technologies can achieve in real-world settings. This body of work explores the innovative and practical applications of AI and behavioral sensing to capture and analyze data for diverse purposes. The first part of the thesis comprises longitudinal studies on behavioral sensing, providing a detailed, long-term view of how …

Towards Scalable Autonomous Underwater Construction With Free-Floating Robots, Samuel Eric Lensgraf

Dartmouth College Ph.D Dissertations

This thesis presents the first free-floating autonomous underwater construction system. Our system built structures weighing up to 100Kg (75Kg in water). Our robot builds structures made of standard cinder blocks and custom designed interlocking cement blocks. It is the first construction robot that uses active buoyancy compensation to efficiently transport building materials. It is also the first construction robot that can reconfigure visual fiducial markers on a foundation during the construction process to expand its working area.

Underwater construction is a challenging problem for free-floating robots. Currents can buffet the robot, and visibility conditions can change. We focus on achieving …

3-D Reconstruction For Underwater Robots With A Monocular Camera And Lights, Monika Roznere

Dartmouth College Ph.D Dissertations

Before a robot can act, it must perceive its environment. Though, this is not a simple task when considering the challenges in underwater domains -- poor visibility conditions, limited sensor configurations, and lack of readily accessible localization. Underwater robots have, nevertheless, improved dramatically with more extensive sensor and navigation equipment. Robot and sensor use have enabled us to explore all reaches of our oceans. On the other hand, these same robots are not easily accessible or transferable to many practical tasks, including fishery management, infrastructure maintenance, disaster response, site conservation, and ecological surveys. There is a growing need for robots …

Automated Cinematographer For Vr Viewing Experiences, Zihan Wu

Dartmouth College Master’s Theses

As the virtual reality (VR) industry continues to evolve, the question of how to effectively capture VR experiences for an audience remains a challenge. The predominant method of showcasing VR applications through first-person recordings lacks cinematic interest, failing to capture other viewpoints and the essence of the moment. Meanwhile, manually setting up cameras and editing videos requires technical expertise on behalf of the user. In this paper, we propose the use of machine learning (ML) to automatically select the most compelling predefined viewpoint in a VR environment, at any given moment. Our models, trained on actor motion and voice volume, …

Advancing Mobile Sensing In Dynamic Environments, Weichen Wang

Dartmouth College Ph.D Dissertations

This thesis presents a comprehensive exploration of enhancing mobile sensing capabilities to address various aspects of human behavior, mental health, personality, social functioning and beyond. We redesign the StudentLife app to improve its sensing efficiency and dependability, enabling support for multi-year-long studies. By adopting new app design, this study addresses the technical challenges of continuous sensing and enhances system robustness. The work is organized into several key studies that collectively aim to expand the scope of mobile sensing in diverse and complex environments.

The first study broadens the scope of mobile sensing to assess personality traits, exploring the potential of …

On Adaptivity And Randomness For Streaming Algorithms, Manuel Stoeckl

Dartmouth College Ph.D Dissertations

A streaming algorithm has a limited amount of memory and reads a long sequence (data stream) of input elements, one by one, and computes an output depending on the input. Such algorithms may be used in an online fashion, producing a sequence of intermediate outputs corresponding to the prefixes of the data stream. Adversarially robust streaming algorithms are required to give correct outputs with a desired probability even when the data stream is adaptively generated by an adversary that can see all intermediate outputs of the algorithm. This thesis binds together research on a variety of problems related to the …

Design, Analysis, And Drop Assembly Of Interlocking Rigid Bodies, Amy K. Sniffen

Dartmouth College Ph.D Dissertations

This work presents a system of interlocking blocks that can be used to build a wide variety of structures. The blocks slide together to form structures that interlock geometrically like a puzzle to form semi-permanent structures without the need for cement or friction lock. The blocks are designed to be easy to fabricate, assemble, and disassemble. Contributions of the block designs include a novel interlocking joint structure; the joints are wedge-shaped, allowing for error mitigation during assembly and allowing structures to be assembled without jamming even if there is manufacturing error. We introduce planar, 3D, and volumetric designs using these …

Exploring Tokenization Techniques To Optimize Patch-Based Time-Series Transformers, Gabriel L. Asher

Computer Science Senior Theses

Transformer architectures have revolutionized deep learning, impacting natural language processing and computer vision. Recently, PatchTST has advanced long-term time-series forecasting by embedding patches of time-steps to use as tokens for transformers. This study examines and seeks to enhance PatchTST's embedding techniques. Using eight benchmark datasets, we explore explore novel token embedding techniques. To this end, we introduce several PatchTST variants, which alter the embedding methods of the original paper. These variants consist of the following architectural changes: using CNNs to embed inputs to tokens, embedding an aggregate measure like the mean, max, or sum of a patch, adding the exponential …

(Meta-)Physical Artworks: Digital Augmentation In Art Observation, Macy A. Toppan

Dartmouth College Master’s Theses

Augmented art— the subgenre of art that incorporates physical and digital artwork— is a rapidly growing field driven by advancing technology and a new generation for whom that tech is a given. Yet the presence of media like augmented and virtual reality in exhibition remains a controversial subject. Rather than focusing on the many theoretical debates about whether digital pieces can qualify as "good" art, we study it in practice through the eyes of the casual art observer. This paper highlights the audience in a within-participant study that asked viewers to take in a physical sculpture intentionally built with virtual …