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Description
Due to the internet being in its infancy, there is no consensus regarding policy approaches that various countries have taken. These policies range from strict government control to liberal access to the internet which makes protecting individual private data difficult. There are too many loopholes and various forms of policy on how to approach protecting data. There must be effort by both the individual, government, and private entities by using theoretical mixed methods to approach protecting oneself properly online.
ContributorsPeralta, Christina A (Author) / Scheall, Scott (Thesis advisor) / Hollinger, Keith (Thesis advisor) / Alozie, Nicholas (Committee member) / Arizona State University (Publisher)
Created2023
Description
The honors thesis explores the relationship between academic majors and the entrepreneurial mindset, focusing on whether Computer Science students have a perceived edge. The study involves a survey of 121 diverse Arizona State University students, complemented by in-depth interviews with 12 participants across various majors. Insights reveal the complex interplay of psychological factors influencing major selection, with Computer Science students advocating for more entrepreneurship-related courses. Challenges include time constraints for STEM majors in pursuing extracurricular activities and a call for universities to proactively integrate entrepreneurship education. While acknowledging the study's limitations, the thesis emphasizes the need for universities to adapt to changing student mindsets. Despite hurdles, the collective belief is that internal determination and effort drive students forward.
ContributorsAgarwal, Sarthak (Author) / Meuth, Ryan (Thesis director) / Sebold, Brent (Committee member) / Barrett, The Honors College (Contributor)
Created2023-12
Description
Social media platforms provide a rich environment for analyzing user behavior. Recently, deep learning-based methods have been a mainstream approach for social media analysis models involving complex patterns. However, these methods are susceptible to biases in the training data, such as participation inequality. Basically, a mere 1% of users generate the majority of the content on social networking sites, while the remaining users, though engaged to varying degrees, tend to be less active in content creation and largely silent. These silent users consume and listen to information that is propagated on the platform.However, their voice, attitude, and interests are not reflected in the online content, making the decision of the current methods predisposed towards the opinion of the active users. So models can mistake the loudest users for the majority. To make the silent majority heard is to reveal the true landscape of the platform. In this dissertation, to compensate for this bias in the data, which is related to user-level data scarcity, I introduce three pieces of research work. Two of these proposed solutions deal with the data on hand while the other tries to augment the current data. Specifically, the first proposed approach modifies the weight of users' activity/interaction in the input space, while the second approach involves re-weighting the loss based on the users' activity levels during the downstream task training. Lastly, the third approach uses large language models (LLMs) and learns the user's writing behavior to expand the current data. In other words, by utilizing LLMs as a sophisticated knowledge base, this method aims to augment the silent user's data.
ContributorsKarami, Mansooreh (Author) / Liu, Huan (Thesis advisor) / Sen, Arunabha (Committee member) / Davulcu, Hasan (Committee member) / Mancenido, Michelle V. (Committee member) / Arizona State University (Publisher)
Created2023
ContributorsDeliwala, Dheeti (Author) / Bryan, Chris (Thesis director) / Strickland, James (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor) / School of Politics and Global Studies (Contributor)
Created2023-12
ContributorsDeliwala, Dheeti (Author) / Bryan, Chris (Thesis director) / Strickland, James (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor) / School of Politics and Global Studies (Contributor)
Created2023-12
Description
Human civilization within the last two decades has largely transformed into an online one, with many of its associated activities taking place on computers and complex networked systems -- their analog and real-world equivalents having been rendered obsolete.These activities run the gamut from the ordinary and mundane, like ordering food, to complex and large-scale, such as those involving critical infrastructure or global trade and communications.
Unfortunately, the activities of human civilization also involve criminal, adversarial, and malicious ones with the result that they also now have their digital equivalents.
Ransomware, malware, and targeted cyberattacks are a fact of life today and are instigated not only by organized criminal gangs, but adversarial nation-states and organizations as well.
Needless to say, such actions result in disastrous and harmful real-world consequences. As the complexity and variety of software has evolved, so too has the ingenuity of attacks that exploit them; for example modern cyberattacks typically involve sequential exploitation of multiple software vulnerabilities.Compared to a decade ago, modern software stacks on personal computers, laptops, servers, mobile phones, and even Internet of Things (IoT) devices involve a dizzying array of interdependent programs and software libraries, with each of these components presenting attractive attack-surfaces for adversarial actors.
However, the responses to this still rely on paradigms that can neither react quickly enough nor scale to increasingly dynamic, ever-changing, and complex software environments.
Better approaches are therefore needed, that can assess system readiness and vulnerabilities, identify potential attack vectors and strategies (including ways to counter them), and proactively detect vulnerabilities in complex software before they can be exploited. In this dissertation, I first present a mathematical model and associated algorithms to identify attacker strategies for sequential cyberattacks based on attacker state, attributes and publicly-available vulnerability information.Second, I extend the model and design algorithms to help identify defensive courses of action against attacker strategies.
Finally, I present my work to enhance the ability of coverage-based fuzzers to identify software vulnerabilities by providing visibility into complex, internal program-states.
ContributorsPaliath, Vivin Suresh (Author) / Doupe, Adam (Thesis advisor) / Shoshitaishvili, Yan (Thesis advisor) / Wang, Ruoyu (Committee member) / Shakarian, Paulo (Committee member) / Arizona State University (Publisher)
Created2023
Description
When looking at drawings of graphs, questions about graph density, community structures, local clustering and other graph properties may be of critical importance for analysis. While graph layout algorithms have focused on minimizing edge crossing, symmetry, and other such layout properties, there is not much known about how these algorithms relate to a user’s ability to perceive graph properties for a given graph layout. This study applies previously established methodologies for perceptual analysis to identify which graph drawing layout will help the user best perceive a particular graph property. A large scale (n = 588) crowdsourced experiment is conducted to investigate whether the perception of two graph properties (graph density and average local clustering coefficient) can be modeled using Weber’s law. Three graph layout algorithms from three representative classes (Force Directed - FD, Circular, and Multi-Dimensional Scaling - MDS) are studied, and the results of this experiment establish the precision of judgment for these graph layouts and properties. The findings demonstrate that the perception of graph density can be modeled with Weber’s law. Furthermore, the perception of the average clustering coefficient can be modeled as an inverse of Weber’s law, and the MDS layout showed a significantly different precision of judgment than the FD layout.
ContributorsSoni, Utkarsh (Author) / Maciejewski, Ross (Thesis advisor) / Kobourov, Stephen (Committee member) / Sefair, Jorge (Committee member) / Arizona State University (Publisher)
Created2018
The Intercoupling of Thermal Transport and Mechanical Properties in Colloidal Nanocrystal Assemblies
Description
Colloidal nanocrystals (NCs) are promising candidates for a wide range of applications (electronics, optoelectronics, photovoltaics, thermoelectrics, etc.). Mechanical and thermal transport property play very important roles in all of these applications. On one hand, mechanical robustness and high thermal conductivity are desired in electronics, optoelectronics, and photovoltaics. This improves thermomechanical stability and minimizes the temperature rise during the device operation. On the other hand, low thermal conductivity is desired for higher thermoelectric figure of merit (ZT). This dissertation demonstrates that ligand structure and nanocrystal ordering are the primary determining factors for thermal transport and mechanical properties in colloidal nanocrystal assemblies. To eliminate the mechanics and thermal transport barrier, I first propose a ligand crosslinking method to improve the thermal transport across the ligand-ligand interface and thus increasing the overall thermal conductivity of NC assemblies. Young’s modulus of nanocrystal solids also increases simultaneously upon ligand crosslinking. My thermal transport measurements show that the thermal conductivity of the iron oxide NC solids increases by a factor of 2-3 upon ligand crosslinking. Further, I demonstrate that, though with same composition, long-range ordered nanocrystal superlattices possess higher mechanical and thermal transport properties than disordered nanocrystal thin films. Experimental measurements along with theoretical modeling indicate that stronger ligand-ligand interaction in NC superlattice accounts for the improved mechanics and thermal transport. This suggests that NC/ligand arranging order also plays important roles in determining mechanics and thermal transport properties of NC assemblies. Lastly, I show that inorganic ligand functionalization could lead to tremendous mechanical enhancement (a factor of ~60) in NC solids. After ligand exchange and drying, the short inorganic Sn2S64- ligands dissociate into a few atomic layers of amorphous SnS2 at room temperature and interconnects the neighboring NCs. I observe a reverse Hall-Petch relation as the size of NC decreases. Both atomistic simulations and analytical phase mixture modeling identify the grain boundaries and their activities as the mechanic bottleneck.
ContributorsWang, Zhongyong (Author) / Wang, Robert RW (Thesis advisor) / Wang, Liping LW (Committee member) / Newman, Nathan NN (Committee member) / Arizona State University (Publisher)
Created2021
Description
Over the past few years, research into the use of doped diamond in electronics has seen an exponential growth. In the course of finding ways to reduce the contact resistivity, nanocarbon materials have been an interesting focus. In this work, the transfer length method (TLM) was used to investigate Ohmic contact properties using the tri-layer stack Ti/Pt/Au on nitrogen-doped n-type conducting nano-carbon (nanoC) layers grown on (100) diamond substrates. The nanocarbon material was characterized using Secondary Ion Mass Spectrometry (SIMS), Scanning electron Microscopy (SEM) X-ray diffraction (XRD), Raman scattering and Hall effect measurements to probe the materials characteristics. Room temperature electrical measurements were taken, and samples were annealed to observe changes in electrical conductivity. Low specific contact resistivity values of 8 x 10^-5 Ωcm^2 were achieved, which was almost two orders of magnitude lower than previously reported values. The results were attributed to the increased nitrogen incorporation, and the presence of electrically active defects which leads to an increase in conduction in the nanocarbon. Further a study of light phosphorus doped layers using similar methods with Ti/Pt/Au contacts again yielded a low contact resistivity of about 9.88 x 10^-2 Ωcm^2 which is an interesting prospect among lightly doped diamond films for applications in devices such as transistors. In addition, for the first time, hafnium was substituted for Ti in the contact stack (Hf/Pt/Au) and studied on nitrogen doped nanocarbon films, which resulted in low contact resistivity values on the order of 10^-2 Ωcm^2. The implications of the results were discussed, and recommendations for improving the experimental process was outlined. Lastly, a method for the selective area growth of nanocarbon was developed and studied and the results provided an insight into how different characterizations can be used to confirm the presence of the nanocrystalline diamond material, the limitations due to the film thickness was explored and ideas for future work was proposed.
ContributorsAmonoo, Evangeline Abena (Author) / Thornton, Trevor (Thesis advisor) / Alford, Terry L (Thesis advisor) / Anwar, Shahriar (Committee member) / Theodore, David (Committee member) / Arizona State University (Publisher)
Created2023
Description
American Sign Language (ASL) is used for Deaf and Hard of Hearing (DHH) individuals to communicate and learn in a classroom setting. In ASL, fingerspelling and gestures are two primary components used for communication. Fingerspelling is commonly used for words that do not have a specifically designated sign or gesture. In technical contexts, such as Computer Science curriculum, there are many technical terms that fall under this category. Most of its jargon does not have standardized ASL gestures; therefore, students, educators, and interpreters alike have been reliant on fingerspelling, which poses challenges for all parties. This study investigates the efficacy of both fingerspelling and gestures with fifteen technical terms that do have standardized gestures. The terms’ fingerspelling and gesture are assessed based on preference, ease of use, ease of learning, and time by research subjects who were selected as DHH individuals familiar with ASL.
The data is collected in a series of video recordings by research subjects as well as a post-participation questionnaire. Each research subject has produced thirty total videos, two videos to fingerspell and gesture each technical term. Afterwards, they completed a post-participation questionnaire in which they indicated their preference and how easy it was to learn and use both fingerspelling and gestures. Additionally, the videos have been analyzed to determine the time difference between fingerspelling and gestures. Analysis reveals that gestures are favored over fingerspelling as they are generally preferred, considered easier to learn and use, and faster. These results underscore the significance for standardized gestures in the Computer Science curriculum for accessible learning that enhances communication and promotes inclusion.
ContributorsKarim, Bushra (Author) / Gupta, Sandeep (Thesis director) / Hossain, Sameena (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor) / School of International Letters and Cultures (Contributor)
Created2024-05