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Undergraduate Research Opportunities Program

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Office of Undergraduate Education

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Publication Search Results

Now showing 1 - 10 of 84

MACH2: System for Root Cause Analysis of Kernel Vulnerabilities

(Georgia Institute of Technology, 2021-12) Desai, Sidhesh

Kernel code is ubiquitous in the modern technology landscape, and therefore, enforcing its security is of high importance. A common problem among modern kernel fuzzers is the discovery of vulnerabilities whose causes are difficult to pinpoint, meaning that they cannot easily be patched by developers. This leads to a large accumulation of bugs for kernel and kernel driver code. This issue can be remediated by being able to trace the root cause of a given exploit in the original source code. This study introduces MACH2, a system through which kernel vulnerabilities can have their root causes pinpointed such that they can be easily corrected by developers and/or automated systems. The MACH2 system consists of a 2-stage process: first, the system generates a trace of the exploit being run, and then, it uses this trace in tandem with a DSE engine to find the input regions of the code corresponding to the vulnerability at hand. MACH2 has already demonstrated its usability against CVEs and real-world exploits, and with upcoming additions, will be able to handle a wide array of vulnerability classes, allowing for a more secure kernel code landscape.
Chainsaw Before Scalpel: Dependency-Based Pre-processing for Program Reduction

(Georgia Institute of Technology, 2021-12) Rousskov, Mark

Program reduction techniques, which aim to minimize the size of a program, have many applications, including software debloating, debugging, and optimization in general. Therefore, these techniques have been extensively studied for decades. Past work in this area has typically focused on either performing larger, more effective edits (e.g., Delta Debugging, Hierarchical Delta Debugging) or reducing the search space based on a language grammar (e.g., Perses, C-Reduce). Most of these techniques had a primary goal of minimal output size, with reduction speed only as a secondary goal. We propose Chainsaw, a novel approach that improves existing techniques by offloading a subset of the reduction to a pre-processing step. Since Chainsaw does not need to be as thorough as existing reducers, this creates an opportunity to take a new approach which can benefit overall end-to-end performance. Our key insight is that in practical application, a considerable amount of input code is not needed, and dependency analysis enables effective and fast identification of this removable code. This dependency analysis is both general, thus easily applicable to different languages, and inexpensive, thus amenable to a speedy pre-processing step. Such analysis can enable the higher-fidelity techniques previously developed to skip a significant quantity of work and produce better results more quickly. We also present a prototype tool based on our approach. Our tool finds unused sections of code by analyzing the dependencies between items in the input text and is straightforward to implement. We leverage existing analysis tooling via the Language Server Protocol to easily identify dependencies. Our initial results are promising and show that our approach is extremely fast and can yield up to twofold end-to-end speed improvement when used as a pre-processor with existing state-of-the-art techniques.
Compositional analysis of laser welds in a Cu46.5Zr46.5A7 glass forming alloy

(Georgia Institute of Technology, 2021-12) Holberton, Harrison Tyler

Laser additive manufacturing is a promising manufacturing method of bulk metallic glasses. Study and understanding of the heat affected zone and fusion zones are crucial in developing this manufacturing technique. A cast Cu46.5Zr46.5A7 sample was processed at laser powers and scan speeds varying from 75-370W and 100-900 mm/s respectively to determine the effects of processing parameters on weld composition for use in additive manufacturing. Copper content was found to generally decrease through the weld fusion zone, and increase through the heat affected zone. Zinc was unexpectedly present in analysis. Cracking occurred at significantly different linear energy densities and appeared to correlate more strongly with laser power at these parameters, supporting previous research that using energy density alone to predict additive manufacturing processes.
A Study Exploring the Relationship Between Racial Discrimination, Depression, Anxiety, and Stress on Sleep Quality

(Georgia Institute of Technology, 2021-12) Rampally, Lolasri

Prior studies have shown that discrimination experiences have a positive association on adults' symptoms of depression, anxiety, and stress as well as on their sleep patterns. Symptoms of depression, anxiety, and stress appear to be associated with age, with younger adults experiencing higher levels of discrimination than older adults. The findings of this study may aid in evaluating the validity of prior literature and also exploring this further by studying the relationship between discrimination and symptoms of depression, stress, and anxiety with gender as a moderating variable. The present study is the first to examine COVID-19's effects on symptoms of depression, anxiety, stress, sleep patterns, and discrimination, which may have been caused by the pandemic. A total of 582 people between the ages of 18 and 79 participated in this study. In part 1 of the study, participants were asked to complete online questionnaires such as DASS for symptoms of depression, anxiety, and stress, PSQI for Pittsburgh Sleep Quality Index, DI for discriminatory index, and general questions about how their lives have been affected by COVID-19. After 48 hours, the participants take part in the second part of the experiment, during which they complete a questionnaire about stress coping strategies and a memory test for the images they've seen in the first part of the experiment. Three hierarchical regression analyses are performed to investigate whether adding variables such as DI, age and gender could significantly increase the variance accounted for in the outcome/criterion variables (i.e., PSQI and DASS). While there is a statistically significant relationship between DASS and PSQI, DI and DASS with age as a moderator, and DI and DASS with gender, the inclusion of the interaction terms for DI and gender or DI and age were not statistically significant indicating that there is no interaction effect which explains variance above and beyond the two independent variables separately. Future studies may modify parts of this study to observe race-related differences, such as increasing the sample size or changing the DI by adding race as a moderator variable.
An Application for Urban Analytics

(Georgia Institute of Technology, 2021-12) Steinichen, Charlotte Jane

The objective of this research was to develop a new, data-based methodology for analyzing urban environments. By combining graph-based street network data with socioeconomic data scraped from open sources such as Google Places and Foursquare, the application designed for this study provides a quantitative understanding of the urban landscape surrounding stadium projects. The application has been shown to be flexible and can be applied to urban environments across the globe. As a result, this study is a promising first step towards a comprehensive, data-based urban model that can be used to assist place-making professionals both in understanding existing urban development and in siting new projects.
Optimal-horizon model-predictive control with differential dynamic programming

(Georgia Institute of Technology, 2021-12) Stachowicz, Kyle W.

We present an algorithm, based on the Differential Dynamic Programming framework, to handle trajectory optimization problems in which the horizon is determined online rather than fixed a priori. This algorithm exhibits exact one-step convergence for linear, quadratic, time-invariant problems and is fast enough for real-time nonlinear model-predictive control. We show derivations for the nonlinear algorithm in the discrete-time case, and apply this algorithm to a variety of nonlinear problems. Finally, we show the efficacy of the optimal-horizon model-predictive control scheme compared to a standard MPC controller, on an obstacle-avoidance problem with planar robots.
Biomechanical Characterization of the Human Tricuspid Apparatus

(Georgia Institute of Technology, 2021-12) Stewart, Cheyenne Victoria Josephine

Tricuspid regurgitation is a form of cardiovascular illness that affects over 1.6 million people in the United States. This condition is more often discovered once it becomes symptomatic, which is usually much too late in its progression and indicative of poor prognosis in the patient. Medical approaches to address this issue typically involve surgical intervention or transcatheter repair and replacement therapies, but there is still a significant lack of knowledge on how current treatments affect biomechanical characteristics of the tricuspid apparatus in humans. This study aims to provide biomechanical data surrounding the human tricuspid valve, including leaflet biaxial tensile response and chordae tendinae uniaxial failure testing response. This data will provide further insight as how to characterize the tricuspid apparatus and inform engineering decisions in future transcatheter valve therapies to address tricuspid regurgitation and improve patient prognosis. Human tricuspid leaflets and chordae are compared to previously tested porcine data. Resultantly, both species share some morphological similarities. However, human leaflet mechanical data recorded in this study exhibited statistically different trends between leaflets compared to porcine data, further emphasizing the need for additional work using human samples in investigating engineering solutions for heart valve disease.
Generation of T cell lines expressing wild type and mutant CD3ε FRET sensors and characterization of CD3ε regulation by plasma membrane binding

(Georgia Institute of Technology, 2021-12) Choi, Yujin

T cells are a crucial part of our adaptive immune response by protecting our system against pathogens and cancer. They recognize specific foreign peptides on the surface of antigen presenting cells (APC) through T cell receptors (TCR) placed on the surface of T cells. Peptides bound to major histocompatibility complexes (pMHC) form bonds with these TCR and allow them to recognize antigen fragments, eventually activating the T cells. In their resting state, the CD3ε and ζ tails are bound to the inner leaflet of the plasma membrane (PM) by ionic interactions, which prevents phosphorylation. TCR-pMHC bond formation allows for CD3 tails’ dissociation from the PM, as observed through Fluorescence Resonance Energy Transfer (FRET). This study aims to create a new, improved FRET pair between CD3ε and PM for wild-type CD3ε as well as a panel of mutated CD3ε which target key steps in the chain of events following TCR-pMHC bond formation until ITAM phosphorylation by Lck, with the hope of elucidating the mechanism of TCR triggering and signal transduction from the extracellular binding site to the intracellular tyrosines. FRET pair for the wild-type CD3ε was created through lentiviral transfection of Jurkat cells through spinfection, followed by single cell sorting conducted with Fluorescence-activated cell sorting (FACS) Aria Fusion machine. Transduced cells expressing Green Fluorescent Protein (GFP) were selected through gating and then diluted into ~0.5 cells/well to be seeded onto a 96 well plate. Top 3 cells were selected for GFP strength and proliferated, thus creating stable cell lines for the wild-type CD3ε FRET pair. CD3ε mutation constructs of the K76T, ITAM, BRS, and RK motifs were then created using polymerase chain reaction (PCR) to insert the mutations in pLenti virus (pLv) and pTwist plasmids. The formation of colonies after transformation and the sequencing results indicate that the mutations were successfully and correctly inserted in the plasmids for each type of mutations: K76T, BRS, and ITAM. Since these plasmids are confirmed for their integrity through sequencing, they will be used to create stable cell lines expressing mutated CD3ε for the new FRET pair. The stable cell lines will be produced through transfection of HEK 293T cells, followed by transduction of Jurkat cells using virus harvested post-transfection. These stable cell lines expressing mutated CD3ε will then be used to explore the mechanism underpinning peptide strength-dependent CD3ε-PM release and its role in antigen recognition in the future.
Overgeneral autobiographical memory in depression: a three-level meta-analysis

(Georgia Institute of Technology, 2021-12) Weiss-Cowie, Samuel Aaron

Overgeneral Autobiographical Memory (OGM) is a frequently studied phenomenon in major depressive disorder (MDD). Although there exist several meta-analyses on OGM and MDD, their emphasis on clinically diagnosed current depression leaves open question about the severity of OGM in subthreshold and remitted depression. In addition, numerous studies of OGM have remained unconsidered due to a focus on one testing paradigm, the Autobiographical Memory Test (AMT). To address these gaps, we conducted a meta-analysis on OGM in MDD that included remitted, subthreshold, and currently depressed samples and incorporated non-AMT studies. In addition, we used three level models for the first time, which enabled robust variance analyses including multiple effect sizes from each study while controlling for dependencies across those effect sizes. With results from a total of 67 published and unpublished works, ours is the largest meta-analysis to date on OGM in depression. We simultaneously identified decreased autobiographical memory specificity (g = -0.73) and increased categoricity (g = 0.77) for depressed individuals compared to controls. Moderator analyses suggested that OGM is more severe in current, clinical MDD than subthreshold and remitted depression, while OGM is similarly severe for positive, neutral, and negative memories. Our results resolve longstanding debate surrounding the relationship between valence and OGM while emphasizing the importance of utilizing a broader range of testing paradigms and considering non-clinical depression in future work.
CATIONIC BOVINE SERUM ALBUMIN NANOPARTICLES FOR DELIVERY OF SIRNA TO FIBROBLASTS

(Georgia Institute of Technology, 2021-12) Lowrey, Lanier C.

Gene regulation through small interfering RNA (siRNA) is a useful way to improve therapeutics and treat diseases. However, since siRNA is rapidly degraded by nucleases in the bloodstream and is anionic and highly hydrophilic, it is not readily taken up by cells. Therefore, a variety of delivery systems that encapsulate siRNA are being developed to overcome these limitations. Protein nanoparticles have the potential to effectively deliver siRNA because siRNA can be encapsulated during the fabrication process. In this work, we have encapsulated siRNA inside 200 nm cationic bovine serum albumin (cBSA) nanoparticles. The positive charge on the cBSA protein enables the negative charge of the siRNA to electrostatically attract, creating a more stable nanoparticle. We measured nanoparticle uptake and intracellular delivery to GFP-3T3 cells using a combination of flow cytometry and fluorescence knockdown assays. cBSA protein nanoparticles are an innovative way to encapsulate siRNA, with the ability to adjust the amount of siRNA in the nanoparticle as needed and stable attraction of siRNA and cBSA protein.