Computer Sciences Commons^™

Computational Environment For Modeling And Analysing Network Traffic Behaviour Using The Divide And Recombine Framework, Ashrith Barthur

Open Access Dissertations

There are two essential goals of this research. The first goal is to design and construct a computational environment that is used for studying large and complex datasets in the cybersecurity domain. The second goal is to analyse the Spamhaus blacklist query dataset which includes uncovering the properties of blacklisted hosts and understanding the nature of blacklisted hosts over time.

The analytical environment enables deep analysis of very large and complex datasets by exploiting the divide and recombine framework. The capability to analyse data in depth enables one to go beyond just summary statistics in research. This deep analysis is …

Lagrangian Analysis Of Vector And Tensor Fields: Algorithmic Foundations And Applications In Medical Imaging And Computational Fluid Dynamics, Zi'ang Ding

Open Access Dissertations

Both vector and tensor fields are important mathematical tools used to describe the physics of many phenomena in science and engineering. Effective vector and tensor field visualization techniques are therefore needed to interpret and analyze the corresponding data and achieve new insight into the considered problem. This dissertation is concerned with the extraction of important structural properties from vector and tensor datasets. Specifically, we present a unified approach for the characterization of distinguished manifolds that form the skeleton of vector and tensor fields and play a key role in understanding their properties.

This dissertation makes several important contributions in this …

Low Rank Methods For Optimizing Clustering, Yangyang Hou

Open Access Dissertations

Complex optimization models and problems in machine learning often have the majority of information in a low rank subspace. By careful exploitation of these low rank structures in clustering problems, we find new optimization approaches that reduce the memory and computational cost.

We discuss two cases where this arises. First, we consider the NEO-K-Means (Non-Exhaustive, Overlapping K-Means) objective as a way to address overlapping and outliers in an integrated fashion. Optimizing this discrete objective is NP-hard, and even though there is a convex relaxation of the objective, straightforward convex optimization approaches are too expensive for large datasets. We utilize low …

Securing Cloud-Based Data Analytics: A Practical Approach, Julian James Stephen

Open Access Dissertations

The ubiquitous nature of computers is driving a massive increase in the amount of data generated by humans and machines. The shift to cloud technologies is a paradigm change that offers considerable financial and administrative gains in the effort to analyze these data. However, governmental and business institutions wanting to tap into these gains are concerned with security issues. The cloud presents new vulnerabilities and is dominated by new kinds of applications, which calls for new security solutions. In the direction of analyzing massive amounts of data, tools like MapReduce, Apache Storm, Dryad and higher-level scripting languages like Pig Latin …

Security Techniques For Sensor Systems And The Internet Of Things, Daniele Midi

Open Access Dissertations

Sensor systems are becoming pervasive in many domains, and are recently being generalized by the Internet of Things (IoT). This wide deployment, however, presents significant security issues.

We develop security techniques for sensor systems and IoT, addressing all security management phases. Prior to deployment, the nodes need to be hardened. We develop nesCheck, a novel approach that combines static analysis and dynamic checking to efficiently enforce memory safety on TinyOS applications. As security guarantees come at a cost, determining which resources to protect becomes important. Our solution, OptAll, leverages game-theoretic techniques to determine the optimal allocation of security resources in …

Graphlet Based Network Analysis, Mahmudur Rahman

Open Access Dissertations

The majority of the existing works on network analysis, study properties that are related to the global topology of a network. Examples of such properties include diameter, power-law exponent, and spectra of graph Laplacians. Such works enhance our understanding of real-life networks, or enable us to generate synthetic graphs with real-life graph properties. However, many of the existing problems on networks require the study of local topological structures of a network.

Graphlets which are induced small subgraphs capture the local topological structure of a network effectively. They are becoming increasingly popular for characterizing large networks in recent years. Graphlet based …

Differentially Private Data Publishing For Data Analysis, Dong Su

Open Access Dissertations

In the information age, vast amounts of sensitive personal information are collected by companies, institutions and governments. A key technological challenge is how to design mechanisms for effectively extracting knowledge from data while preserving the privacy of the individuals involved. In this dissertation, we address this challenge from the perspective of differentially private data publishing. Firstly, we propose PrivPfC, a differentially private method for releasing data for classification. The key idea underlying PrivPfC is to privately select, in a single step, a grid, which partitions the data domain into a number of cells. This selection is done using the exponential …

Divide And Recombined For Large Complex Data: Nonparametric-Regression Modelling Of Spatial And Seasonal-Temporal Time Series, Xiaosu Tong

Open Access Dissertations

In the first chapter of this dissertation, I briefly introduce one type of nonparametric regression method, namely local polynomial regression, followed by emphasis on one specific application of loess on time series decomposition, called Seasonal Trend Loess (STL). The chapter is closed by the introduction of D\&R; (Divide and Recombined) statistical framework. Data can be divided into subsets, each of which is applied with a statistical analysis method. This is an embarrassing parallel procedure since there is no communication between each subset. Then the analysis result for each subset are combined together to be the final analysis outcome for the …

Students' Explanations In Complex Learning Of Disciplinary Programming, Camilo Vieira

Open Access Dissertations

Computational Science and Engineering (CSE) has been denominated as the third pillar of science and as a set of important skills to solve the problems of a global society. Along with the theoretical and the experimental approaches, computation offers a third alternative to solve complex problems that require processing large amounts of data, or representing complex phenomena that are not easy to experiment with. Despite the relevance of CSE, current professionals and scientists are not well prepared to take advantage of this set of tools and methods. Computation is usually taught in an isolated way from engineering disciplines, and therefore, …

Inter-Color Npr Lines: A Comparison Of Rendering Techniques, Donald G. Herring

Open Access Theses

Renders of 3D scenes can feature lines drawn automatically along sharp edges between colored areas on object textures, in order to imitate certain conventional styles of hand-drawn line art. However, such "inter-color lines" have been studied very little. Two algorithms for rendering these lines were compared in this study - a faster one utilizing lines baked into the textures themselves and a more complex one that dynamically generated the lines in image space on each frame - for the purpose of determining which of the two better imitated traditional, hand-drawn art styles and which was more visually appealing. Test subjects …

Video Annotation By Crowd Workers With Privacy-Preserving Local Disclosure, Apeksha Dipak Kumavat

Open Access Theses

Advancements in computer vision are still not reliable enough for detecting video content including humans and their actions. Microtask crowdsourcing on task markets such as Amazon Mechnical Turk and Upwork can bring humans into the loop. However, engaging crowd workers to annotate non-public video footage risks revealing the identities of people in the video who may have a right to anonymity.

This thesis demonstrates how we can engage untrusted crowd workers to detect behaviors and objects, while robustly concealing the identities of all faces. We developed a web-based system that presents obfuscated videos to crowd workers, and provides them with …

Deep Collective Inference, John A. Moore

Open Access Theses

Collective inference is widely used to improve classification in network datasets. However, despite recent advances in deep learning and the successes of recurrent neural networks (RNNs), researchers have only just recently begun to study how to apply RNNs to heterogeneous graph and network datasets. There has been recent work on using RNNs for unsupervised learning in networks (e.g., graph clustering, node embedding) and for prediction (e.g., link prediction, graph classification), but there has been little work on using RNNs for node-based relational classification tasks. In this paper, we provide an end-to-end learning framework using RNNs for collective inference. Our main …

Just In Time Assembly (Jita) - A Run Time Interpretation Approach For Achieving Productivity Of Creating Custom Accelerators In Fpgas, Sen Ma

Graduate Theses and Dissertations

The reconfigurable computing community has yet to be successful in allowing programmers to access FPGAs through traditional software development flows. Existing barriers that prevent programmers from using FPGAs include: 1) knowledge of hardware programming models, 2) the need to work within the vendor specific CAD tools and hardware synthesis. This thesis presents a series of published papers that explore different aspects of a new approach being developed to remove the barriers and enable programmers to compile accelerators on next generation reconfigurable manycore architectures. The approach is entitled Just In Time Assembly (JITA) of hardware accelerators. The approach has been defined …

Automatic Assessment Of Environmental Hazards For Fall Prevention Using Smart-Cameras, Jeffrey Kutchka

Graduate Theses and Dissertations

As technology advances in the field of Computer Vision, new applications will emerge. One device that has emerged is the smart-camera, a camera attached to an embedded system that can perform routines a regular camera could not, such as object or event detection. In this thesis we describe a smart-camera system we designed, implemented, and evaluated for fall prevention monitoring of at-risk people while in bed, whether it be for a hospital patient, nursing home resident, or at home elderly resident. The camera will give a nurse or caregiver environmental awareness of the at-risk person and notify them when that …

Using Machine Learning To Predict Student Achievement On The State Of Texas Assessment Of Academic Readiness Examination In Charter Schools, Christopher D. Gonzalez

Theses and Dissertations

The purpose of this study was to research and develop a way to use machine learning algorithms (MLAs) to predict student achievement on the State of Texas Assessment of Academic Readiness (STAAR), specifically in the charter school setting. Charter schools have the disadvantage of a constant influx in students, so providing historical student data in order to analyze trends proves difficult. This study expands on previous research done on students in secondary and post-secondary school and determining features that indicate success in these settings. The data used is from the district of IDEA Public Schools who focuses on providing education …

An Open Source Approach To Serve A Large Number Of Computer Users Using Block-Level Streaming, Max D. Torres

Theses and Dissertations

There are several options for providing a large number of computers to users for their daily tasks. A typical setup may consist of a large number of computers where each relies on an HDD consisting of the required software, sufficient RAM, a capable CPU that meets the software requirements, and a stable network connection. This thesis proposes the use of the open-source AoE protocol to stream an OS to a user computer from a central server. Since the streaming is done from a well-protected central storage, the AoE protocol is less prone to failures compared to the traditional approach based …

Anxiolytic Effects Of Propranolol And Diphenoxylate On Mice And Automated Stretch-Attend Posture Analysis, Kevin Scott Holly

Doctoral Dissertations

The prevention of social anxiety, performance anxiety, and social phobia via the combination of two generic drugs, diphenoxylate HC1 (opioid) plus atropine sulfate (anticholinergic) and propranolol HCl (beta blocker) was evaluated in mice through behavioral studies. A patent published on a September 8, 2011 by Benjamin D. Holly, US 2011/0218215 Al, prompted the research. The drug combination of diphenoxylate and atropine plus propranolol could be an immediate treatment for patients suffering from acute phobic and social anxiety disorders. Demonstrating the anxiolytic effects of the treatment on mice would validate a mouse model for neuroscientist to be used to detect the …

A Study Of Security Issues Of Mobile Apps In The Android Platform Using Machine Learning Approaches, Lei Cen

Open Access Dissertations

Mobile app poses both traditional and new potential threats to system security and user privacy. There are malicious apps that may do harm to the system, and there are mis-behaviors of apps, which are reasonable and legal when not abused, yet may lead to real threats otherwise. Moreover, due to the nature of mobile apps, a running app in mobile devices may be only part of the software, and the server side behavior is usually not covered by analysis. Therefore, direct analysis on the app itself may be incomplete and additional sources of information are needed. In this dissertation, we …

Knowledge Modeling Of Phishing Emails, Courtney Falk

Open Access Dissertations

This dissertation investigates whether or not malicious phishing emails are detected better when a meaningful representation of the email bodies is available. The natural language processing theory of Ontological Semantics Technology is used for its ability to model the knowledge representation present in the email messages. Known good and phishing emails were analyzed and their meaning representations fed into machine learning binary classifiers. Unigram language models of the same emails were used as a baseline for comparing the performance of the meaningful data. The end results show how a binary classifier trained on meaningful data is better at detecting phishing …

Improving Cloud Middlebox Infrastructure For Online Services, Rohan S. Gandhi

Open Access Dissertations

Middleboxes are an indispensable part of the datacenter networks that provide high availability, scalability and performance to the online services. Using load balancer as an example, this thesis shows that the prevalent scale-out middlebox designs using commodity servers are plagued with three fundamental problems: (1) The server-based layer-4 middleboxes are costly and inflate round-trip-time as much as 2x by processing the packets in software. (2) The middlebox instances cause traffic detouring en route from sources to destinations, which inflates network bandwidth usage by as much as 3.2x and can cause transient congestion. (3) Additionally, existing cloud providers do not support …

Interactive Logical Analysis Of Planning Domains, Rajesh Kalyanam

Open Access Dissertations

Humans exhibit a significant ability to answer a wide range of questions about previously unencountered planning domains, and leverage this ability to construct “general-purpose'' solution plans for the domain.

The long term vision of this research is to automate this ability, constructing a system that utilizes reasoning to automatically verify claims about a planning domain. The system would use this ability to automatically construct and verify a generalized plan to solve any planning problem in the domain. The goal of this thesis is to start with baseline results from the interactive verification of claims about planning domains and develop the …

Controlling For Confounding Network Properties In Hypothesis Testing And Anomaly Detection, Timothy La Fond

Open Access Dissertations

An important task in network analysis is the detection of anomalous events in a network time series. These events could merely be times of interest in the network timeline or they could be examples of malicious activity or network malfunction. Hypothesis testing using network statistics to summarize the behavior of the network provides a robust framework for the anomaly detection decision process. Unfortunately, choosing network statistics that are dependent on confounding factors like the total number of nodes or edges can lead to incorrect conclusions (e.g., false positives and false negatives). In this dissertation we describe the challenges that face …

Data Driven Low-Bandwidth Intelligent Control Of A Jet Engine Combustor, Nathan L. Toner

Open Access Dissertations

This thesis introduces a low-bandwidth control architecture for navigating the input space of an un-modeled combustor system between desired operating conditions while avoiding regions of instability and blow-out. An experimental procedure is discussed for identifying regions of instability and gathering sufficient data to build a data-driven model of the system's operating modes. Regions of instability and blow-out are identified experimentally and a data-driven operating point classifier is designed. This classifier acts as a map of the operating space of the combustor, indicating regions in which the flame is in a "good" or "bad" operating mode. A data-driven predictor is also …

Improving The Eco-System Of Passwords, Weining Yang

Open Access Dissertations

Password-based authentication is perhaps the most widely used method for user authentication. Passwords are both easy to understand and use, and easy to implement. With these advantages, password-based authentication is likely to stay as an important part of security in the foreseeable future. One major weakness of password-based authentication is that many users tend to choose weak passwords that are easy to guess. In this dissertation, we address the challenge and improve the eco-system of passwords in multiple aspects. Firstly, we provide methodologies that help password research. To be more specific, we propose Probability Threshold Graphs, which is superior to …

An Anomaly-Based Intrusion Detection System Based On Artificial Immune System (Ais) Techniques, Harish Valayapalayam Kumaravel

Open Access Theses

Two of the major approaches to intrusion detection are anomaly-based detection and signature-based detection. Anomaly-based approaches have the potential for detecting zero-day and other new forms of attacks. Despite this capability, anomaly-based approaches are comparatively less widely used when compared to signature-based detection approaches. Higher computational overhead, higher false positive rates, and lower detection rates are the major reasons for the same. This research has tried to mitigate this problem by using techniques from an area called the Artificial Immune Systems (AIS). AIS is a collusion of immunology, computer science and engineering and tries to apply a number of techniques …

Using Ubiquitous Data To Improve Smartwatches' Context Awareness, Yuankun Song

Open Access Theses

Nowadays, more and more data is being generated by various software applications, services and smart devices every second. The data contains abundant information about people’s daily lives. This research explored the possibility of improving smartwatches’ context awareness by using common ubiquitous data. The researcher developed a prototype system consisting of an Android application and a web application, and conducted an experiment where 10 participants performed several tasks with the help of a smartwatch. The result showed a significant improvement of the smartwatch’s context awareness running the prototype application, which used ubiquitous data to automatically execute proper actions according to contexts. …

Hardware Accelerated Authentication System For Dynamic Time-Critical Networks, Ankush Singla

Open Access Theses

The secure and efficient operation of time-critical networks, such as vehicular networks, smart-grid and other smart-infrastructures, is of primary importance in today’s society. It is crucial to minimize the impact of security mechanisms over such networks so that the safe and reliable operations of time-critical systems are not being interfered.

Even though there are several security mechanisms, their application to smart-infrastructure and Internet of Things (IoT) deployments may not meet the ubiquitous and time-sensitive needs of these systems. That is, existing security mechanisms either introduce a significant computation and communication overhead, or they are not scalable for a large number …

Packet Filter Performance Monitor (Anti-Ddos Algorithm For Hybrid Topologies), Ibrahim M. Waziri

Open Access Dissertations

DDoS attacks are increasingly becoming a major problem. According to Arbor Networks, the largest DDoS attack reported by a respondent in 2015 was 500 Gbps. Hacker News stated that the largest DDoS attack as of March 2016 was over 600 Gbps, and the attack targeted the entire BBC website.

With this increasing frequency and threat, and the average DDoS attack duration at about 16 hours, we know for certain that DDoS attacks will not be going away anytime soon. Commercial companies are not effectively providing mitigation techniques against these attacks, considering that major corporations face the same challenges. Current security …

Learning Program Specifications From Sample Runs, He Zhu

Open Access Dissertations

With science fiction of yore being reality recently with self-driving cars, wearable computers and autonomous robots, software reliability is growing increasingly important. A critical pre-requisite to ensure the software that controls such systems is correct is the availability of precise specifications that describe a program's intended behaviors. Generating these specifications manually is a challenging, often unsuccessful, exercise; unfortunately, existing static analysis techniques often produce poor quality specifications that are ineffective in aiding program verification tasks.

In this dissertation, we present a recent line of work on automated synthesis of specifications that overcome many of the deficiencies that plague existing specification …

Detection Of Communication Over Dnssec Covert Channels, Nicole M. Hands

Open Access Theses

Unauthorized data removal and modification from information systems represents a major and formidable threat in modern computing. Security researchers are engaged in a constant and escalating battle with the writers of malware and other methods of network intrusion to detect and mitigate this threat. Advanced malware behaviors include encryption of communications between the server and infected client machines as well as various strategies for resilience and obfuscation of infrastructure. These techniques evolve to use any and all available mechanisms. As the Internet has grown, DNS has been expanded and has been given security updates. This study analyzed the potential uses …