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ASU Electronic Theses and Dissertations


This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.

In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.

Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.


Language
  • English
Resource Type
  • Masters Thesis
Date Range
2010 2018


Machine learning tutorials often employ an application and runtime specific solution for a given problem in which users are expected to have a broad understanding of data analysis and software programming. This thesis focuses on designing and implementing a new, hands-on approach to teaching machine learning by streamlining the process of generating Inertial Movement Unit (IMU) data from multirotor flight sessions, training a linear classifier, and applying said classifier to solve Multi-rotor Activity Recognition (MAR) problems in an online lab setting. MAR labs leverage cloud computing and data storage technologies to host a versatile environment capable of logging, orchestrating, and …

Contributors
De La Rosa, Matthew Lee, Chen, Yinong, Collofello, James, et al.
Created Date
2018

With the increasing complexity of computing systems and the rise in the number of risks and vulnerabilities, it is necessary to provide a scalable security situation awareness tool to assist the system administrator in protecting the critical assets, as well as managing the security state of the system. There are many methods to provide security states' analysis and management. For instance, by using a Firewall to manage the security state, and/or a graphical analysis tools such as attack graphs for analysis. Attack Graphs are powerful graphical security analysis tools as they provide a visual representation of all possible attack scenarios …

Contributors
Sabur, Abdulhakim, Huang, Dijiang, Zhang, Yancho, et al.
Created Date
2018

There currently exist various challenges in learning cybersecuirty knowledge, along with a shortage of experts in the related areas, while the demand for such talents keeps growing. Unlike other topics related to the computer system such as computer architecture and computer network, cybersecurity is a multidisciplinary topic involving scattered technologies, which yet remains blurry for its future direction. Constructing a knowledge graph (KG) in cybersecurity education is a first step to address the challenges and improve the academic learning efficiency. With the advancement of big data and Natural Language Processing (NLP) technologies, constructing large KGs and mining concepts, from unstructured …

Contributors
Lin, Fanjie, Huang, Dijiang, Hsiao, I-Han, et al.
Created Date
2018

The advent of the Internet of Things (IoT) and its increasing appearances in Small Office/Home Office (SOHO) networks pose a unique issue to the availability and health of the Internet at large. Many of these devices are shipped insecurely, with poor default user and password credentials and oftentimes the general consumer does not have the technical knowledge of how they may secure their devices and networks. The many vulnerabilities of the IoT coupled with the immense number of existing devices provide opportunities for malicious actors to compromise such devices and use them in large scale distributed denial of service attacks, …

Contributors
Chang, Laurence Hao, Yau, Stephen, Doupe, Adam, et al.
Created Date
2018

Smart cities are the next wave of rapid expansion of Internet of Things (IoT). A smart city is a designation given to a city that incorporates information and communication technologies (ICT) to enhance the quality and performance of urban services, such as energy, transportation, healthcare, communications, entertainments, education, e-commerce, businesses, city management, and utilities, to reduce resource consumption, wastage and overall costs. The overarching aim of a smart city is to enhance the quality of living for its residents and businesses, through technology. In a large ecosystem, like a smart city, many organizations and companies collaborate with the smart city …

Contributors
Mishra, Vineet, Yau, Sik-Sang, Goul, Michael K, et al.
Created Date
2017

Recent trends in big data storage systems show a shift from disk centric models to memory centric models. The primary challenges faced by these systems are speed, scalability, and fault tolerance. It is interesting to investigate the performance of these two models with respect to some big data applications. This thesis studies the performance of Ceph (a disk centric model) and Alluxio (a memory centric model) and evaluates whether a hybrid model provides any performance benefits with respect to big data applications. To this end, an application TechTalk is created that uses Ceph to store data and Alluxio to perform …

Contributors
NAGENDRA, SHILPA, Huang, Dijiang, Zhao, Ming, et al.
Created Date
2017

Today the information technology systems have addresses, software stacks and other configuration remaining unchanged for a long period of time. This paves way for malicious attacks in the system from unknown vulnerabilities. The attacker can take advantage of this situation and plan their attacks with sufficient time. To protect our system from this threat, Moving Target Defense is required where the attack surface is dynamically changed, making it difficult to strike. In this thesis, I incorporate live migration of Docker container using CRIU (checkpoint restore) for moving target defense. There are 460K Dockerized applications, a 3100% growth over 2 years[1]. …

Contributors
Bohara, Bhakti, Huang, Dijiang, Doupe, Adam, et al.
Created Date
2017

Scientific workflows allow scientists to easily model and express the entire data processing steps, typically as a directed acyclic graph (DAG). These scientific workflows are made of a collection of tasks that usually take a long time to compute and that produce a considerable amount of intermediate datasets. Because of the nature of scientific exploration, a scientific workflow can be modified and re-run multiple times, or new scientific workflows are created that might make use of past intermediate datasets. Storing intermediate datasets has the potential to save time in computations. Since storage is limited, one main problem that needs a …

Contributors
de Armas, Jadiel, Bazzi, Rida, Huang, Dijiang, et al.
Created Date
2017

Passwords are ubiquitous and are poised to stay that way due to their relative usability, security and deployability when compared with alternative authentication schemes. Unfortunately, humans struggle with some of the assumptions or requirements that are necessary for truly strong passwords. As administrators try to push users towards password complexity and diversity, users still end up using predictable mangling patterns on old passwords and reusing the same passwords across services; users even inadvertently converge on the same patterns to a surprising degree, making an attacker’s job easier. This work explores using machine learning techniques to pick out strong passwords from …

Contributors
Todd, Margaret Nicole, Xue, Guoliang, Ahn, Gail-Joon, et al.
Created Date
2016

Detecting cyber-attacks in cyber systems is essential for protecting cyber infrastructures from cyber-attacks. It is very difficult to detect cyber-attacks in cyber systems due to their high complexity. The accuracy of the attack detection in the cyber systems depends heavily on the completeness of the collected sensor information. In this thesis, two approaches are presented: one to detecting attacks in completely observable cyber systems, and the other to estimating types of states in partially observable cyber systems for attack detection in cyber systems. These two approaches are illustrated using three large data sets of network traffic because the packet-level information …

Contributors
Guha, Sayantan, Yau, Stephen S., Ahn, Gail-Joon, et al.
Created Date
2016