Computer Sciences Commons^™

A Small-Scale Testbed For Large-Scale Reliable Computing, Jason R. St. John

Open Access Theses

High performance computing (HPC) systems frequently suffer errors and failures from hardware components that negatively impact the performance of jobs run on these systems. We analyzed system logs from two HPC systems at Purdue University and created statistical models for memory and hard disk errors. We created a small-scale error injection testbed—using a customized QEMU build, libvirt, and Python—for HPC application programmers to test and debug their programs in a faulty environment so that programmers can write more robust and resilient programs before deploying them on an actual HPC system. The deliverables for this project are the fault injection program, …

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 …

A Framework For The Statistical Analysis Of Mass Spectrometry Imaging Experiments, Kyle Bemis

Open Access Dissertations

Mass spectrometry (MS) imaging is a powerful investigation technique for a wide range of biological applications such as molecular histology of tissue, whole body sections, and bacterial films , and biomedical applications such as cancer diagnosis. MS imaging visualizes the spatial distribution of molecular ions in a sample by repeatedly collecting mass spectra across its surface, resulting in complex, high-dimensional imaging datasets. Two of the primary goals of statistical analysis of MS imaging experiments are classification (for supervised experiments), i.e. assigning pixels to pre-defined classes based on their spectral profiles, and segmentation (for unsupervised experiments), i.e. assigning pixels to newly …

Visual Analytics Of Location-Based Social Networks For Decision Support, Junghoon Chae

Open Access Dissertations

Recent advances in technology have enabled people to add location information to social networks called Location-Based Social Networks (LBSNs) where people share their communication and whereabouts not only in their daily lives, but also during abnormal situations, such as crisis events. However, since the volume of the data exceeds the boundaries of human analytical capabilities, it is almost impossible to perform a straightforward qualitative analysis of the data. The emerging field of visual analytics has been introduced to tackle such challenges by integrating the approaches from statistical data analysis and human computer interaction into highly interactive visual environments. Based on …

Combinatorial Algorithms For Perturbation Theory And Application On Quantum Computing, Yudong Cao

Open Access Dissertations

Quantum computing is an emerging area between computer science and physics. Numerous problems in quantum computing involve quantum many-body interactions. This dissertation concerns the problem of simulating arbitrary quantum many-body interactions using realistic two-body interactions. To address this issue, a general class of techniques called perturbative reductions (or perturbative gadgets) is adopted from quantum complexity theory and in this dissertation these techniques are improved for experimental considerations. The idea of perturbative reduction is based on the mathematical machinery of perturbation theory in quantum physics. A central theme of this dissertation is then to analyze the combinatorial structure of the perturbation …

Hybrid Stm/Htm For Nested Transactions In Java, Keith G. Chapman

Open Access Dissertations

Transactional memory (TM) has long been advocated as a promising pathway to more automated concurrency control for scaling concurrent programs running on parallel hardware. Software TM (STM) has the benefit of being able to run general transactional programs, but at the significant cost of overheads imposed to log memory accesses, mediate access conflicts, and maintain other transaction metadata. Recently, hardware manufacturers have begun to offer commodity hardware TM (HTM) support in their processors wherein the transaction metadata is maintained “for free” in hardware. However, HTM approaches are only best-effort: they cannot successfully run all transactional programs, whether because of hardware …

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 …

Effective Memory Management For Mobile Environments, Ahmed Mohamed Abd-Elhaffiez Hussein

Open Access Dissertations

Smartphones, tablets, and other mobile devices exhibit vastly different constraints compared to regular or classic computing environments like desktops, laptops, or servers. Mobile devices run dozens of so-called “apps” hosted by independent virtual machines (VM). All these VMs run concurrently and each VM deploys purely local heuristics to organize resources like memory, performance, and power. Such a design causes conflicts across all layers of the software stack, calling for the evaluation of VMs and the optimization techniques specific for mobile frameworks.

In this dissertation, we study the design of managed runtime systems for mobile platforms. More specifically, we deepen the …

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 …

What Broke Where For Distributed And Parallel Applications — A Whodunit Story, Subrata Mitra

Open Access Dissertations

Detection, diagnosis and mitigation of performance problems in today's large-scale distributed and parallel systems is a difficult task. These large distributed and parallel systems are composed of various complex software and hardware components. When the system experiences some performance or correctness problem, developers struggle to understand the root cause of the problem and fix in a timely manner. In my thesis, I address these three components of the performance problems in computer systems. First, we focus on diagnosing performance problems in large-scale parallel applications running on supercomputers. We developed techniques to localize the performance problem for root-cause analysis. Parallel applications, …

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 …

Convicted By Memory: Automatically Recovering Spatial-Temporal Evidence From Memory Images, Brendan D. Saltaformaggio

Open Access Dissertations

Memory forensics can reveal “up to the minute” evidence of a device’s usage, often without requiring a suspect’s password to unlock the device, and it is oblivious to any persistent storage encryption schemes, e.g., whole disk encryption. Prior to my work, researchers and investigators alike considered data-structure recovery the ultimate goal of memory image forensics. This, however, was far from sufficient, as investigators were still largely unable to understand the content of the recovered evidence, and hence efficiently locating and accurately analyzing such evidence locked in memory images remained an open research challenge.

In this dissertation, I propose breaking from …

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 …

Impact Of Myh6 Variants In Hypoplastic Left Heart Syndrome, Aoy Tomita-Mitchell, Karl D. Stamm, Donna K. Mahnke, Min-Su Kim, Pip M. Hidestrand, Huan-Ling Liang, Mary A. Goetsch, Mats Hidestrand, Pippa Simpson, Andrew N. Pelech, James S. Tweddell, D. Woodrow Benson, John Lough, Michael Mitchell

Mathematics, Statistics and Computer Science Faculty Research and Publications

Hypoplastic left heart syndrome (HLHS) is a clinically and anatomically severe form of congenital heart disease (CHD). Although prior studies suggest that HLHS has a complex genetic inheritance, its etiology remains largely unknown. The goal of this study was to characterize a risk gene in HLHS and its effect on HLHS etiology and outcome. We performed next-generation sequencing on a multigenerational family with a high prevalence of CHD/HLHS, identifying a rare variant in the α-myosin heavy chain (MYH6) gene. A case-control study of 190 unrelated HLHS subjects was then performed and compared with the 1000 Genomes Project. Damaging …

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 …

A Robust System For Local Reuse Detection Of Arabic Text On The Web, Leena Mahmoud Ahmed Lulu

Theses

We developed techniques for finding local text reuse on the Web, with an emphasis on the Arabic language. That is, our objective is to develop text reuse detection methods that can detect alternative versions of the same information and focus on exploring the feasibility of employing text reuse detection methods on the Web. The results of this research can be thought of as rich tools to information analysts for corporate and intelligence applications. Such tools will become essential parts in validating and assessing information coming from uncertain origins. These tools will prove useful for detecting reuse in scientific literature too. …

Attacking Android Smartphone Systems Without Permissions, Mon Kywe Su, Yingjiu Li, Kunal Petal, Michael Grace

Research Collection School Of Computing and Information Systems

Android requires third-party applications to request for permissions when they access critical mobile resources, such as users' personal information and system operations. In this paper, we present the attacks that can be launched without permissions. We first perform call graph analysis, component analysis and data-flow analysis on various parts of Android framework to retrieve unprotected APIs. Unprotected APIs provide a way of accessing resources without any permissions. We then exploit selected unprotected APIs and launch a number of attacks on Android phones. We discover that without requesting for any permissions, an attacker can access to device ID, phone service state, …

Orienteering Problem: A Survey Of Recent Variants, Solution Approaches And Applications, Aldy Gunawan, Hoong Chuin Lau, Pieter Vansteenwegen

Research Collection School Of Computing and Information Systems

Duplicate record, see https://ink.library.smu.edu.sg/sis_research/3271. The Orienteering Problem (OP) has received a lot of attention in the past few decades. The OP is a routing problem in which the goal is to determine a subset of nodes to visit, and in which order, so that the total collected score is maximized and a given time budget is not exceeded. A number of typical variants has been studied, such as the Team OP, the (Team) OP with Time Windows and the Time Dependent OP. Recently, a number of new variants of the OP was introduced, such as the Stochastic OP, the …

Lexicon Knowledge Extraction With Sentiment Polarity Computation, Zhaoxia Wang, Vincent Joo Chuan Tong, Pingcheng Ruan, Fang Li

Research Collection School Of Computing and Information Systems

Sentiment analysis is one of the most popular natural language processing techniques. It aims to identify the sentiment polarity (positive, negative, neutral or mixed) within a given text. The proper lexicon knowledge is very important for the lexicon-based sentiment analysis methods since they hinge on using the polarity of the lexical item to determine a text's sentiment polarity. However, it is quite common that some lexical items appear positive in the text of one domain but appear negative in another. In this paper, we propose an innovative knowledge building algorithm to extract sentiment lexicon knowledge through computing their polarity value …

Cryptographic Reverse Firewall Via Malleable Smooth Projective Hash Functions, Rongmao Chen, Guomin Yang, Guomin Yang, Willy Susilo, Fuchun Guo, Mingwu Zhang

Research Collection School Of Computing and Information Systems

Motivated by the revelations of Edward Snowden, postSnowden cryptography has become a prominent research direction in recent years. In Eurocrypt 2015, Mironov and Stephens-Davidowitz proposed a novel concept named cryptographic reverse firewall (CRF) which can resist exfiltration of secret information from an arbitrarily compromised machine. In this work, we continue this line of research and present generic CRF constructions for several widely used cryptographic protocols based on a new notion named malleable smooth projective hash function. Our contributions can be summarized as follows. – We introduce the notion of malleable smooth projective hash function, which is an extension of the …

Security Testing With Misuse Case Modeling, Samer Yousef Khamaiseh

Boise State University Theses and Dissertations

Having a comprehensive model of security requirements is a crucial step towards developing a reliable software system. An effective model of security requirements which describes the possible scenarios that may affect the security aspects of the system under development can be an effective approach for subsequent use in generating security test cases.

Misuse case was first proposed by Sinder and Opdahl as an approach to extract the security requirements of the system under development [1]. A misuse case is a use case representing scenarios that might be followed by a system adversary in order to compromise the system; that is …

Developing An Abac-Based Grant Proposal Workflow Management System, Milson Munakami

Boise State University Theses and Dissertations

In the advent of the digital transformation, online business processes need to be automated and modeled as workflows. A workflow typically involves a sequence of coordinated tasks and shared data that need to be secured and protected from unauthorized access. In other words, a workflow can be described simply as the movement of documents and activities through a business process among different users. Such connected flow of information among various users with different permission level offers many benefits along with new challenges. Cyber threats are becoming more sophisticated as skilled and motivated attackers both insiders and outsiders are equipped with …

Massively Parallel Algorithm For Solving The Eikonal Equation On Multiple Accelerator Platforms, Anup Shrestha

Boise State University Theses and Dissertations

The research presented in this thesis investigates parallel implementations of the Fast Sweeping Method (FSM) for Graphics Processing Unit (GPU)-based computational plat forms and proposes a new parallel algorithm for distributed computing platforms with accelerators. Hardware accelerators such as GPUs and co-processors have emerged as general- purpose processors in today’s high performance computing (HPC) platforms, thereby increasing platforms’ performance capabilities. This trend has allowed greater parallelism and substantial acceleration of scientific simulation software. In order to leverage the power of new HPC platforms, scientific applications must be written in specific lower-level programming languages, which used to be platform specific. Newer …

Vulnerability Analysis And Security Framework For Zigbee Communication In Iot, Charbel Azzi

UNLV Theses, Dissertations, Professional Papers, and Capstones

Securing IoT (Internet of Things) systems in general, regardless of the communication technology used, has been the concern of many researchers and private companies. As for ZigBee security concerns, much research and many experiments have been conducted to better predict the nature of potential security threats. In this research we are addressing several ZigBee vulnerabilities by performing first hand experiments and attack simulations on ZigBee protocol. This will allow us to better understand the security issues surveyed and find ways to mitigate them. Based on the attack simulations performed and the survey conducted, we have developed a ZigBee IoT framework …

Acoustic Detection, Source Separation, And Classification Algorithms For Unmanned Aerial Vehicles In Wildlife Monitoring And Poaching, Carlo Lopez-Tello

UNLV Theses, Dissertations, Professional Papers, and Capstones

This work focuses on the problem of acoustic detection, source separation, and classification under noisy conditions. The goal of this work is to develop a system that is able to detect poachers and animals in the wild by using microphones mounted on unmanned aerial vehicles (UAVs). The classes of signals used to detect wildlife and poachers include: mammals, birds, vehicles and firearms. The noise signals under consideration include: colored noises, UAV propeller and wind noises.

The system consists of three sub-systems: source separation (SS), signal detection, and signal classification. Non-negative Matrix Factorization (NMF) is used for source separation, and random …

Novel Non-Blocking Approach For A Concurrent Heap, Rashmi Niyolia

UNLV Theses, Dissertations, Professional Papers, and Capstones

We present a non-blocking algorithm for a concurrent heap in asynchronous shared memory multiprocessors. Processors in these machines often execute instructions at varying speeds and are subject to arbitrarily long delays. Our implementation supports Non-blocking Insert, Delete, and Find-Min operations on a heap. Non-blocking techniques avoid the drawbacks associated with mutual exclusion and also admit improved parallelism. Insert and DeleteMin operations in heap take more than one atomic instruction to complete, thus, it is possible that a new operation may be started before the previous one completes, leaving heap inconsistent between operations. We have represented heap as an array of …

Simulation Of Online Bin Packing In Practice, Kalpana Rajagopal

UNLV Theses, Dissertations, Professional Papers, and Capstones

The bin packing problem requires packing a set of objects into a finite number of bins of fixed capacity in a way that minimizes the number of bins used. We consider the online version of the problem where items arrive over tine and a decision has to be made as soon as an element is available. Online algorithms can be analyzed in terms of competitiveness, a measure of performance that compares the solution obtained online with the optimal offline solution for the same problem, where the lowest possible competitiveness is best. Online processing is difficult due to the fact that …

A Case Study On Enterprise Content Management Using Agile Methodology, Rohit Raj

UNLV Theses, Dissertations, Professional Papers, and Capstones

Every organization has the need to create, classify, manage and archive information so that it is accessible when they need it. The amount of data or information needed for an organization to build their business and for them to be more positive in today’s business world is increasing exponentially, which also includes unstructured data or unstructured content. It is not appropriate only to “manage” content, but whether the correct version of the data or document or record can be accessed. Enterprise Content Management is an efficient collection and planning of information that is to be used by a very particular …

Enhancing The Draft Assembly With Minhash, Saju Varghese

UNLV Theses, Dissertations, Professional Papers, and Capstones

In this thesis, we report on the use of minhash techniques to improve the draft assembly of a genome mapping. More specifically, we use minhash to compare the scaffolds of sea urchin and sea cucumber genomes.

One of the main contributions of this thesis is the implementation of minhash with the Message Passing Interface (MPI) utilizing Intel Phi co-processors. It is shown that our implementation significantly reduces the processing time for identification of k-mer similarities.