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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.


Date Range
2011 2019


Machine learning (ML) and deep neural networks (DNNs) have achieved great success in a variety of application domains, however, despite significant effort to make these networks robust, they remain vulnerable to adversarial attacks in which input that is perceptually indistinguishable from natural data can be erroneously classified with high prediction confidence. Works on defending against adversarial examples can be broadly classified as correcting or detecting, which aim, respectively at negating the effects of the attack and correctly classifying the input, or detecting and rejecting the input as adversarial. In this work, a new approach for detecting adversarial examples is proposed. …

Contributors
Sun, Lin, Bazzi, Rida, Li, Baoxin, et al.
Created Date
2019

For systems having computers as a significant component, it becomes a critical task to identify the potential threats that the users of the system can present, while being both inside and outside the system. One of the most important factors that differentiate an insider from an outsider is the fact that the insider being a part of the system, owns privileges that enable him/her access to the resources and processes of the system through valid capabilities. An insider with malicious intent can potentially be more damaging compared to outsiders. The above differences help to understand the notion and scope of …

Contributors
Nolastname, Sharad, Bazzi, Rida, Sen, Arunabha, et al.
Created Date
2019

Due to large data resources generated by online educational applications, Educational Data Mining (EDM) has improved learning effects in different ways: Students Visualization, Recommendations for students, Students Modeling, Grouping Students, etc. A lot of programming assignments have the features like automating submissions, examining the test cases to verify the correctness, but limited studies compared different statistical techniques with latest frameworks, and interpreted models in a unified approach. In this thesis, several data mining algorithms have been applied to analyze students’ code assignment submission data from a real classroom study. The goal of this work is to explore and predict students’ …

Contributors
Tian, Wenbo, Hsiao, Ihan, Bazzi, Rida, et al.
Created Date
2019

Distributed systems are prone to attacks, called Sybil attacks, wherein an adversary may generate an unbounded number of bogus identities to gain control over the system. In this thesis, an algorithm, DownhillFlow, for mitigating such attacks is presented and tested experimentally. The trust rankings produced by the algorithm are significantly better than those of the distributed SybilGuard protocol and only slightly worse than those of the best-known Sybil defense algorithm, ACL. The results obtained for ACL are consistent with those obtained in previous studies. The running times of the algorithms are also tested and two results are obtained: first, DownhillFlow’s …

Contributors
Bradley, Michael, Bazzi, Rida, Richa, Andrea, et al.
Created Date
2018

Phishing is a form of online fraud where a spoofed website tries to gain access to user's sensitive information by tricking the user into believing that it is a benign website. There are several solutions to detect phishing attacks such as educating users, using blacklists or extracting phishing characteristics found to exist in phishing attacks. In this thesis, we analyze approaches that extract features from phishing websites and train classification models with extracted feature set to classify phishing websites. We create an exhaustive list of all features used in these approaches and categorize them into 6 broader categories and 33 …

Contributors
Namasivayam, Bhuvana Lalitha, Bazzi, Rida, Zhao, Ziming, et al.
Created Date
2017

Data from a total of 282 online web applications was collected, and accounts for 230 of those web applications were created in order to gather data about authentication practices, multistep authentication practices, security question practices, fallback authentication practices, and other security practices for online accounts. The account creation and data collection was done between June 2016 and April 2017. The password strengths for online accounts were analyzed and password strength data was compared to existing data. Security questions used by online accounts were evaluated for security and usability, and fallback authentication practices were assessed based on their adherence to best …

Contributors
Gutierrez, Garrett, Bazzi, Rida, Ahn, Gail-Joon, 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

The success of Bitcoin has generated significant interest in the financial community to understand whether the technological underpinnings of the cryptocurrency paradigm can be leveraged to improve the efficiency of financial processes in the existing infrastructure. Various alternative proposals, most notably, Ripple and Ethereum, aim to provide solutions to the financial community in different ways. These proposals derive their security guarantees from either the computational hardness of proof-of-work or voting based distributed consensus mechanism, both of which can be computationally expensive. Furthermore, the financial audit requirements for a participating financial institutions have not been suitably addressed. This thesis presents a …

Contributors
Gupta, Saurabh, Bazzi, Rida, Ahn, Gail-Joon, et al.
Created Date
2016

For the past three decades, the design of an effective strategy for generating poetry that matches that of a human’s creative capabilities and complexities has been an elusive goal in artificial intelligence (AI) and natural language generation (NLG) research, and among linguistic creativity researchers in particular. This thesis presents a novel approach to fixed verse poetry generation using neural word embeddings. During the course of generation, a two layered poetry classifier is developed. The first layer uses a lexicon based method to classify poems into types based on form and structure, and the second layer uses a supervised classification method …

Contributors
Magge Ranganatha, Arjun, Syrotiuk, Violet R, Baral, Chitta, et al.
Created Date
2016

Several decades of transistor technology scaling has brought the threat of soft errors to modern embedded processors. Several techniques have been proposed to protect these systems from soft errors. However, their effectiveness in protecting the computation cannot be ascertained without accurate and quantitative estimation of system reliability. Vulnerability -- a metric that defines the probability of system-failure (reliability) through analytical models -- is the most effective mechanism for our current estimation and early design space exploration needs. Previous vulnerability estimation tools are based around the Sim-Alpha simulator which has been to shown to have several limitations. In this thesis, I …

Contributors
Tanikella, Srinivas Karthik, Shrivastava, Aviral, Bazzi, Rida, et al.
Created Date
2016

Knowledge representation and reasoning is a prominent subject of study within the field of artificial intelligence that is concerned with the symbolic representation of knowledge in such a way to facilitate automated reasoning about this knowledge. Often in real-world domains, it is necessary to perform defeasible reasoning when representing default behaviors of systems. Answer Set Programming is a widely-used knowledge representation framework that is well-suited for such reasoning tasks and has been successfully applied to practical domains due to efficient computation through grounding--a process that replaces variables with variable-free terms--and propositional solvers similar to SAT solvers. However, some domains provide …

Contributors
Bartholomew, Michael James, Lee, Joohyung, Bazzi, Rida, et al.
Created Date
2016

Robotic technology is advancing to the point where it will soon be feasible to deploy massive populations, or swarms, of low-cost autonomous robots to collectively perform tasks over large domains and time scales. Many of these tasks will require the robots to allocate themselves around the boundaries of regions or features of interest and achieve target objectives that derive from their resulting spatial configurations, such as forming a connected communication network or acquiring sensor data around the entire boundary. We refer to this spatial allocation problem as boundary coverage. Possible swarm tasks that will involve boundary coverage include cooperative load …

Contributors
Peruvemba Kumar, Ganesh, Berman, Spring M, Fainekos, Georgios, et al.
Created Date
2016

A load balancer is an essential part of many network systems. A load balancer is capable of dividing and redistributing incoming network traffic to different back end servers, thus improving reliability and performance. Existing load balancing solutions can be classified into two categories: hardware-based or software-based. Hardware-based load balancing systems are hard to manage and force network administrators to scale up (replacing with more powerful but expensive hardware) when their system can not handle the growing traffic. Software-based solutions have a limitation when dealing with a single large TCP flow. In recent years, with the fast developments of virtualization technology, …

Contributors
Wu, Jinxuan, Syrotiuk, Violet R., Bazzi, Rida, et al.
Created Date
2015

On Android, existing security procedures require apps to request permissions for access to sensitive resources. Only when the user approves the requested permissions will the app be installed. However, permissions are an incomplete security mechanism. In addition to a user's limited understanding of permissions, the mechanism does not account for the possibility that different permissions used together have the ability to be more dangerous than any single permission alone. Even if users did understand the nature of an app's requested permissions, this mechanism is still not enough to guarantee that a user's information is protected. Applications can potentially send or …

Contributors
Gibson, Aaron Scott, Bazzi, Rida, Ahn, Gail-Joon, et al.
Created Date
2015

When scientific software is written to specify processes, it takes the form of a workflow, and is often written in an ad-hoc manner in a dynamic programming language. There is a proliferation of legacy workflows implemented by non-expert programmers due to the accessibility of dynamic languages. Unfortunately, ad-hoc workflows lack a structured description as provided by specialized management systems, making ad-hoc workflow maintenance and reuse difficult, and motivating the need for analysis methods. The analysis of ad-hoc workflows using compiler techniques does not address dynamic languages - a program has so few constrains that its behavior cannot be predicted. In …

Contributors
Acuna, Ruben, Bazzi, Rida, Lacroix, Zoe, et al.
Created Date
2015

Internet browsers are today capable of warning internet users of a potential phishing attack. Browsers identify these websites by referring to blacklists of reported phishing websites maintained by trusted organizations like Google, Phishtank etc. On identifying a Unified Resource Locator (URL) requested by a user as a reported phishing URL, browsers like Mozilla Firefox and Google Chrome display an 'active' warning message in an attempt to stop the user from making a potentially dangerous decision of visiting the website and sharing confidential information like username-password, credit card information, social security number etc. However, these warnings are not always successful at …

Contributors
Sharma, Satyabrata, Bazzi, Rida, Walker, Erin, et al.
Created Date
2015

Broadcast Encryption is the task of cryptographically securing communication in a broadcast environment so that only a dynamically specified subset of subscribers, called the privileged subset, may decrypt the communication. In practical applications, it is desirable for a Broadcast Encryption Scheme (BES) to demonstrate resilience against attacks by colluding, unprivileged subscribers. Minimal Perfect Hash Families (PHFs) have been shown to provide a basis for the construction of memory-efficient t-resilient Key Pre-distribution Schemes (KPSs) from multiple instances of 1-resilient KPSs. Using this technique, the task of constructing a large t-resilient BES is reduced to finding a near-minimal PHF of appropriate parameters. …

Contributors
O'Brien, Devon James, Colbourn, Charles J, Bazzi, Rida, et al.
Created Date
2012

This thesis addresses the problem of online schema updates where the goal is to be able to update relational database schemas without reducing the database system's availability. Unlike some other work in this area, this thesis presents an approach which is completely client-driven and does not require specialized database management systems (DBMS). Also, unlike other client-driven work, this approach provides support for a richer set of schema updates including vertical split (normalization), horizontal split, vertical and horizontal merge (union), difference and intersection. The update process automatically generates a runtime update client from a mapping between the old the new schemas. …

Contributors
Tyagi, Preetika, Bazzi, Rida, Candan, Kasim S, et al.
Created Date
2011

Reducing device dimensions, increasing transistor densities, and smaller timing windows, expose the vulnerability of processors to soft errors induced by charge carrying particles. Since these factors are inevitable in the advancement of processor technology, the industry has been forced to improve reliability on general purpose Chip Multiprocessors (CMPs). With the availability of increased hardware resources, redundancy based techniques are the most promising methods to eradicate soft error failures in CMP systems. This work proposes a novel customizable and redundant CMP architecture (UnSync) that utilizes hardware based detection mechanisms (most of which are readily available in the processor), to reduce overheads …

Contributors
Hong, Fei, Shrivastava, Aviral, Bazzi, Rida, et al.
Created Date
2011