Systems Architecture Commons^™

Torsh: Obfuscating Consumer Internet-Of-Things Traffic With A Collaborative Smart-Home Router Network, Adam Vandenbussche

Dartmouth College Undergraduate Theses

When consumers install Internet-connected "smart devices" in their homes, metadata arising from the communications between these devices and their cloud-based service providers enables adversaries privy to this traffic to profile users, even when adequate encryption is used. Internet service providers (ISPs) are one potential adversary privy to users’ incom- ing and outgoing Internet traffic and either currently use this insight to assemble and sell consumer advertising profiles or may in the future do so. With existing defenses against such profiling falling short of meeting user preferences and abilities, there is a need for a novel solution that empowers consumers to …

Out-Of-Core Gpu Path Tracing On Large Instanced Scenes Via Geometry Streaming, Jeremy Berchtold

Master's Theses

We present a technique for out-of-core GPU path tracing of arbitrarily large scenes that is compatible with hardware-accelerated ray-tracing. Our technique improves upon previous works by subdividing the scene spatially into streamable chunks that are loaded using a priority system that maximizes ray throughput and minimizes GPU memory usage. This allows for arbitrarily large scaling of scene complexity. Our system required under 19 minutes to render a solid color version of Disney's Moana Island scene (39.3 million instances, 261.1 million unique quads, and 82.4 billion instanced quads at a resolution of 1024x429 and 1024spp on an RTX 5000 (24GB memory …

Information Provenance For Mobile Health Data, Taylor A. Hardin

Dartmouth College Ph.D Dissertations

Mobile health (mHealth) apps and devices are increasingly popular for health research, clinical treatment and personal wellness, as they offer the ability to continuously monitor aspects of individuals' health as they go about their everyday activities. Many believe that combining the data produced by these mHealth apps and devices may give healthcare-related service providers and researchers a more holistic view of an individual's health, increase the quality of service, and reduce operating costs. For such mHealth data to be considered useful though, data consumers need to be assured that the authenticity and the integrity of the data has remained intact---especially …

Privacy Assessment Breakthrough: A Design Science Approach To Creating A Unified Methodology, Lisa Mckee

Masters Theses & Doctoral Dissertations

Recent changes have increased the need for and awareness of privacy assessments. Organizations focus primarily on Privacy Impact Assessments (PIA) and Data Protection Impact Assessments (DPIA) but rarely take a comprehensive approach to assessments or integrate the results into a privacy risk program. There are numerous industry standards and regulations for privacy assessments, but the industry lacks a simple unified methodology with steps to perform privacy assessments. The objectives of this research project are to create a new privacy assessment methodology model using the design science methodology, update industry standards and present training for conducting privacy assessments that can be …

Two Project On Information Systems Capabilities And Organizational Performance, Giridhar Reddy Bojja

Masters Theses & Doctoral Dissertations

Information systems (IS), as a multi-disciplinary research area, emphasizes the complementary relationship between people, organizations, and technology and has evolved dramatically over the years. IS and the underlying Information Technology (IT) application and research play a crucial role in transforming the business world and research within the management domain. Consistent with this evolution and transformation, I develop a two-project dissertation on Information systems capabilities and organizational outcomes.

Project 1 examines the role of hospital operational effectiveness on the link between information systems capabilities and hospital performance. This project examines the cross-lagged effects on a sample of 217 hospitals measured over …

Comparative Study Of Snort 3 And Suricata Intrusion Detection Systems, Cole Hoover

Computer Science and Computer Engineering Undergraduate Honors Theses

Network Intrusion Detection Systems (NIDS) are one layer of defense that can be used to protect a network from cyber-attacks. They monitor a network for any malicious activity and send alerts if suspicious traffic is detected. Two of the most common open-source NIDS are Snort and Suricata. Snort was first released in 1999 and became the industry standard. The one major drawback of Snort has been its single-threaded architecture. Because of this, Suricata was released in 2009 and uses a multithreaded architecture. Snort released Snort 3 last year with major improvements from earlier versions, including implementing a new multithreaded architecture …

Development Of Classroom Tools For A Risc-V Embedded System, Lucas Phillips

Undergraduate Honors Theses

RISC-V is an open-source instruction set that has been gaining popularity in recent years, and, with support from large chip manufacturers like Intel and the benefits of its open-source nature, RISC-V devices are likely to continue gaining momentum. Many courses in a computer science program involve development on an embedded device. Usually, this device is of the ARM architecture, like a Raspberry Pi. With the increasing use of RISC-V, it may be beneficial to use a RISC-V embedded device in one of these classroom environments. This research intends to assist development on the SiFive HiFive1 RevB, which is a RISC-V …

Using A Bert-Based Ensemble Network For Abusive Language Detection, Noah Ballinger

Computer Science and Computer Engineering Undergraduate Honors Theses

Over the past two decades, online discussion has skyrocketed in scope and scale. However, so has the amount of toxicity and offensive posts on social media and other discussion sites. Despite this rise in prevalence, the ability to automatically moderate online discussion platforms has seen minimal development. Recently, though, as the capabilities of artificial intelligence (AI) continue to improve, the potential of AI-based detection of harmful internet content has become a real possibility. In the past couple years, there has been a surge in performance on tasks in the field of natural language processing, mainly due to the development of …

Rethinking The Design Of Online Professor Reputation Systems, Haley Tatum

LSU Master's Theses

Online Professor Reputation (OPR) systems, such as RateMyProfessors.com (RMP), are frequently used by college students to post and access peer evaluations of their pro- fessors. However, recent evidence has shown that these platforms suffer from major bias problems. Failing to address bias in online professor ratings not only leads to negative expectations and experiences in class, but also poor performance on exams. To address these concerns, in this thesis, we study bias in OPR systems from a software design point of view. At the first phase of our analysis, we conduct a systematic literature review of 23 interdisciplinary studies on …

Multi-Device Data Analysis For Fault Localization In Electrical Distribution Grids, Jacob D L Hunte

Electronic Thesis and Dissertation Repository

The work presented in this dissertation represents work which addresses some of the main challenges of fault localization methods in electrical distribution grids. The methods developed largely assume access to sophisticated data sources that may not be available and that any data sets recorded by devices are synchronized. These issues have created a barrier to the adoption of many solutions by industry. The goal of the research presented in this dissertation is to address these challenges through the development of three elements. These elements are a synchronization protocol, a fault localization technique, and a sensor placement algorithm.

The synchronization protocol …

A False Sense Of Security - Organizations Need A Paradigm Shift On Protecting Themselves Against Apts, Srinivasulu R. Vuggumudi

Masters Theses & Doctoral Dissertations

Organizations Advanced persistent threats (APTs) are the most complex cyberattacks and are generally executed by cyber attackers linked to nation-states. The motivation behind APT attacks is political intelligence and cyber espionage. Despite all the awareness, technological advancements, and massive investment, the fight against APTs is a losing battle for organizations. An organization may implement a security strategy to prevent APTs. However, the benefits to the security posture might be negligible if the measurement of the strategy’s effectiveness is not part of the plan. A false sense of security exists when the focus is on implementing a security strategy but not …

Leaderboard Design Principles Influencing User Engagement In An Online Discussion, Brian S. Bovee

Masters Theses & Doctoral Dissertations

Along with the popularity of gamification, there has been increased interest in using leaderboards to promote engagement with online learning systems. The existing literature suggests that when leaderboards are designed well they have the potential to improve learning, but qualitative investigations are required in order to reveal design principles that will improve engagement. In order to address this gap, this qualitative study aims to explore students' overall perceptions of popular leaderboard designs in a gamified, online discussion. Using two leaderboards reflecting performance in an online discussion, this study evaluated multiple leaderboard designs from student interviews and other data sources regarding …

Improving Adversarial Attacks Against Malconv, Justin Burr

Masters Theses & Doctoral Dissertations

This dissertation proposes several improvements to existing adversarial attacks against MalConv, a raw-byte malware classifier for Windows PE files. The included contributions greatly improve the success rates and performance of gradient-based file overlay attacks. All improvements are included in a new open-source attack utility called BitCamo.

Several new payload initialization strategies for use with gradient-based attacks are proposed and evaluated as potential replacements for the randomized initialization method used by current attacks. An algorithm for determining the optimal payload size is also proposed. The resulting improvements achieve a 100% evasion rate against eligible target executables using an average payload size …

Aligning Recovery Objectives With Organizational Capabilities, Jude C. Ejiobi

Masters Theses & Doctoral Dissertations

To reduce or eliminate the impact of a cyber-attack on an organization, preparations to recover a failed system and/or data are usually made in anticipation of such an attack. To avoid a false sense of security, these preparations should, as closely as possible, reflect the organization’s capabilities, in order to inform future improvement and avoid unattainable goals. There is an absence of a strong basis for the selection of the metrics that are used to measure preparation. Informal and unreliable processes are widely used, and they often result in metrics that conflict with the organization’s capabilities and interests. The goal …

Defining Service Level Agreements In Serverless Computing, Mohamed Elsakhawy

Electronic Thesis and Dissertation Repository

The emergence of serverless computing has brought significant advancements to the delivery of computing resources to cloud users. With the abstraction of infrastructure, ecosystem, and execution environments, users could focus on their code while relying on the cloud provider to manage the abstracted layers. In addition, desirable features such as autoscaling and high availability became a provider’s responsibility and can be adopted by the user's application at no extra overhead.

Despite such advancements, significant challenges must be overcome as applications transition from monolithic stand-alone deployments to the ephemeral and stateless microservice model of serverless computing. These challenges pertain to the …

A Metric For Machine Learning Vulnerability To Adversarial Examples, Matt Bradley

Masters Theses & Doctoral Dissertations

Machine learning is used in myriad aspects, both in academic research and in everyday life, including safety-critical applications such as robust robotics, cybersecurity products, medial testing and diagnosis where a false positive or negative could have catastrophic results. Despite the increasing prevalence of machine learning applications and their role in critical systems we rely on daily, the security and robustness of machine learning models is still a relatively young field of research with many open questions, particularly on the defensive side of adversarial machine learning. Chief among these open questions is how best to quantify a model’s attack surface against …

Nft Sneaker Marketplace Design, Testing, And Challenges, Chris Zhu

Honors Theses

This paper introduces the preliminary background and implementation of the NFT sneaker marketplace. Specifically, we build sneaker NFTs on top of ERC-20 within the Ethereum network and use a top-to-bottom design mechanism. Our website performs well in its functionality, compatibility, and performance. We discuss possible future steps for security implementation. In particular, we recommend using a cold wallet for clients' transactions and implementing multi-signature contracts to avoid spoofing and repudiation. Introducing the sneaker NFT marketplace will vastly reduce the costs of transactions and delivery time in the physical sneaker marketplace. We hope investors in the physical asset space can find …

A New Way To Make Music: Processing Digital Audio In Virtual Reality, Gavin E. Payne

Senior Projects Spring 2022

The work of this project attempts to provide new methods of creating music with technology. The product, Fields, is a functional piece of virtual reality software, providing users an immersive and interactive set of tools used to build and design instruments in a modular manner. Each virtual tool is analogous to musical hardware such as guitar pedals, synthesizers, or samplers, and can be thought of as an effect or instrument on its own. Specific configurations of these virtual audio effects can then be played to produce music, and then even saved by the user to load up and play with …

Virtual Machine Introspection Tool Design Analysis, Justin Martin

Dissertations, Master's Theses and Master's Reports

Virtual machines are an integral part of today’s computing world. Their use is widespread and applicable in many different computing fields. With virtual machines, the ability to introspect and monitor is often overlooked or left unimplemented. Introspection is used to gather information about the state of virtual machines as they operate. Without introspection, verbose log data and state information is unavailable after unexpected errors or crashes occur. With introspection, this data can be analyzed further to determine the true cause of the unexpected crash or error. Therefore, introspection plays a critical role in portraying accurate historical information regarding the operating …

Poor Man’S Trace Cache: A Variable Delay Slot Architecture, Tino C. Moore

Dissertations, Master's Theses and Master's Reports

We introduce a novel fetch architecture called Poor Man’s Trace Cache (PMTC). PMTC constructs taken-path instruction traces via instruction replication in static code and inserts them after unconditional direct and select conditional direct control transfer instructions. These traces extend to the end of the cache line. Since available space for trace insertion may vary by the position of the control transfer instruction within the line, we refer to these fetch slots as variable delay slots. This approach ensures traces are fetched along with the control transfer instruction that initiated the trace. Branch, jump and return instruction semantics as well as …

Smart Decision-Making Via Edge Intelligence For Smart Cities, Nathaniel Hudson

Theses and Dissertations--Computer Science

Smart cities are an ambitious vision for future urban environments. The ultimate aim of smart cities is to use modern technology to optimize city resources and operations while improving overall quality-of-life of its citizens. Realizing this ambitious vision will require embracing advancements in information communication technology, data analysis, and other technologies. Because smart cities naturally produce vast amounts of data, recent artificial intelligence (AI) techniques are of interest due to their ability to transform raw data into insightful knowledge to inform decisions (e.g., using live road traffic data to control traffic lights based on current traffic conditions). However, training and …

Hard Real-Time Linux On A Raspberry Pi For 3d Printing, Alvin Nguyen

Master's Projects

The project presents how a Raspberry Pi with hard real-time enabled Linux can control stepper motors to operate the kinematics of a 3D (three-dimensional) printer. The consistent performance of the Raspberry Pi with the PREEMPT-RT (real-time) patch can satisfy real hard-time requirements for 3D printing kinematics, without introducing dedicated microcontrollers. The Klipper 3D printer firmware enables one of the Raspberry Pi processors to act as the Klipper MCU, the primary controller for the hardware components. This project introduces a software implementation of the control logic for controlling the stepper motors, which utilizes the PCA9685 pwm driver and TB6612 motor drivers …

A Practical Approach To Automated Software Correctness Enhancement, Aleksandr Zakharchenko

Dissertations

To repair an incorrect program does not mean to make it correct; it only means to make it more-correct, in some sense, than it is. In the absence of a concept of relative correctness, i.e. the property of a program to be more-correct than another with respect to a specification, the discipline of program repair has resorted to various approximations of absolute (traditional) correctness, with varying degrees of success. This shortcoming is concealed by the fact that most program repair tools are tested on basic cases, whence making them absolutely correct is not clearly distinguishable from making them relatively more-correct. …

Dynamic Resource Management Of Fog-Cloud Computing For Iot Support, Mariia Surmenok

Master's Projects

The internet of things (IoT) is an integrated part of contemporary life. It includes wearable devices, such as smart watches and cell phones, as well as sensors for Smart City. Fog computing can improve the efficiency and battery life of IoT devices by offloading tasks to fog cloud. It is important to have fog clusters near the IoT device for faster data offload. The goal of this project is to develop dynamic resource allocation for on-demand fog computing cluster to efficiently deploy tasks from IoT. This report studies the different research papers about the current state of resource management in …

Deep Learning Strategies For Pool Boiling Heat Flux Prediction Using Image Sequences, Connor Heo

Graduate Theses and Dissertations

The understanding of bubble dynamics during boiling is critical to the design of advanced heater surfaces to improve the boiling heat transfer. The stochastic bubble nucleation, growth, and coalescence processes have made it challenging to obtain mechanistic models that can predict boiling heat flux based on the bubble dynamics. Traditional boiling image analysis relies on the extraction of the dominant physical quantities from the images and is thus limited to the existing knowledge of these quantities. Recently, machine-learning-aided analysis has shown success in boiling crisis detection, heat flux prediction, real-time image analysis, etc., whereas most of the existing studies are …

Component Damage Source Identification For Critical Infrastructure Systems, Nathan Davis

Graduate Theses and Dissertations

Cyber-Physical Systems (CPS) are becoming increasingly prevalent for both Critical Infrastructure and the Industry 4.0 initiative. Bad values within components of the software portion of CPS, or the computer systems, have the potential to cause major damage if left unchecked, and so detection and locating of where these occur is vital. We further define features of these computer systems and create a use-based system topology. We then introduce a function to monitor system integrity and the presence of bad values as well as an algorithm to locate them. We then show an improved version, taking advantage of several system properties …

Millipyde: A Cross-Platform Python Framework For Transparent Gpu Acceleration, James B. Asbury

Master's Theses

The prevalence of general-purpose GPU computing continues to grow and tackle a wider variety of problems that benefit from GPU-acceleration. This acceleration often suffers from a high barrier to entry, however, due to the complexity of software tools that closely map to the underlying GPU hardware, the fast-changing landscape of GPU environments, and the fragmentation of tools and languages that only support specific platforms. Because of this, new solutions will continue to be needed to make GPGPU acceleration more accessible to the developers that can benefit from it. AMD’s new cross-platform development ecosystem ROCm provides promise for developing applications and …

Memory Forensics Comparison Of Apple M1 And Intel Architecture Using Volatility Framework, Joshua Duke

LSU Master's Theses

Memory forensics allows an investigator to get a full picture of what is occurring on-device at the time that a memory sample is captured and is frequently used to detect and analyze malware. Malicious attacks have evolved from living on disk to having persistence mechanisms in the volatile memory (RAM) of a device and the information that is captured in memory samples contains crucial information for full forensic analysis by cybersecurity professionals. Recently, Apple unveiled computers containing a custom designed system on a chip (SoC) called the M1 that is based on ARM architecture. Our research focused on the differences …

System Design And Optimization For Efficient Flash-Based Caching In Data Centers, Jian Liu

LSU Doctoral Dissertations

Modern data centers are the backbone of today’s Internet-based services and applications. With the explosive growth of the Internet data and a wider range of data-intensive applications being deployed, it is increasingly challenging for data centers to satisfy the ever-increasing demand for high-quality data services. To relieve the heavy burden on data center systems and accelerate data processing, a popular cost-efficient solution is to deploy high-speed, large-capacity flash-based cache systems. However, we are facing multiple critical challenges from device hardware, systems, to application workloads. In this dissertation, we focus on designing highly efficient caching solutions to cope with the explosive …

Scaling Down The Energy Cost Of Connecting Everyday Objects To The Internet, Mohammad Rostami

Doctoral Dissertations

The Internet of Things (IoT) promises new opportunities for better monitoring and control of thousands of objects and sensors in households and industrial applications. The viability of large-scale IoT is, however, still a challenge given that the most widely known options for connecting everyday objects, i.e. duty-cycled active radios such as WiFi, Bluetooth and Zigbee, are power-hungry and increase the cost of deployment and maintenance of the connected devices. The main argument of this thesis is that passive radios that use backscatter communication, which has been used primarily for RFIDs, can fill this gap as an ultra-low power replacement for …