Systems Architecture Commons^™

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 …

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 …

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 …

Computational Complexity Reduction Of Deep Neural Networks, Mee Seong Im, Venkat Dasari

Mathematica Militaris

Deep neural networks (DNN) have been widely used and play a major role in the field of computer vision and autonomous navigation. However, these DNNs are computationally complex and their deployment over resource-constrained platforms is difficult without additional optimizations and customization.

In this manuscript, we describe an overview of DNN architecture and propose methods to reduce computational complexity in order to accelerate training and inference speeds to fit them on edge computing platforms with low computational resources.

Iot Clusters Platform For Data Collection, Analysis, And Visualization Use Case, Soin Abdoul Kassif Baba M Traore

Symposium of Student Scholars

Climate change is happening, and many countries are already facing devastating consequences. Populations worldwide are adapting to the season's unpredictability they relay to lands for agriculture. Our first research was to develop an IoT Clusters Platform for Data Collection, analysis, and visualization. The platform comprises hardware parts with Raspberry Pi and Arduino's clusters connected to multiple sensors. The clusters transmit data collected in real-time to microservices-based servers where the data can be accessed and processed. Our objectives in developing this platform were to create an efficient data collection system, relatively cheap to implement and easy to deploy in any part …

Machine Learning-Oriented Predictive Maintenance (Pdm) Framework For Autonomous Vehicles (Avs): Adopting Blockchain For Pdm Solution, Md Jobair Hossain Faruk, Hossain Shahriar, Maria Valero

Symposium of Student Scholars

Autonomous Vehicles (AVs) refers to smart, connected and multimedia cars with technological megatrends of the fourth industrial revolution (Industry 4.0) and have gained huge strive in today's world. AVs adopt automated driving systems (ADS) technique that permits the vehicle to manage and control driving points without human drivers by utilizing advanced equipment including a combination of sensors, controllers, onboard computers, actuators, algorithms, and advanced software embedded in the different parts of the vehicle. These advanced sensors provide unique inputs to the ADS to generate a path from point A to point B. Ensuring the safety of sensors by limiting maintenance …

Students Certification Management (Scm): Hyperledger Fabric-Based Digital Repository, Md Jobair Hossain Faruk, Hossain Shahriar, Maria Valero

Symposium of Student Scholars

The higher education sector has been heavily impacted financially by the economic downturn caused by the pandemic that has resulted a decline in student enrollments. Finding cost-effective novel technology for storing and sharing student's credentials among academic institutions and potential employers is a demand. Within the current conventional approach, ensuring authentication of a candidate’s credentials is costly and time-consuming which gives burdens to thousands of prospective students and potential employees. As a result, candidates fail to secure opportunities for either delay or non-submission of credentials all over the world. Blockchain technology has the potential for students' control over their credentials; …

A Review Of Dark Web: Crawling And Discovery Of Information, Timothy Williams, Edwin Matthew, Juanjo Rodriguez-Cardenas, Jack Wright, Hossain Shahriar

Symposium of Student Scholars

The dark web is often discussed in taboo by many who are unfamiliar with the subject. However, this essay takes a dive into the skeleton of what constructs the dark web by compiling the research of published essays. TOR and other discussed browsers are specialized web browsers that provide anonymity by going through multiple servers and encrypted networks between the host and client, hiding the IP address of both ends. This provides difficulty in terms of controlling or monitoring the dark web, leading to its popularity in criminal underworlds.

In this work, we provide an overview of data mining and …

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 …

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 …

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 …

Passing Time And Syncing Secrets: Demonstrating Covert Channel Vulnerabilities In Precision Time Protocol (Ptp), Aron J. Smith-Donovan

Mathematics, Statistics, and Computer Science Honors Projects

Covert channels use steganographic approaches to transfer secret digital communications; when applied to network protocols, these strategies can facilitate undetectable data exfiltration and insertion attacks. Because covert channel techniques are protocol- and implementation-specific, individual case studies are necessary to assess for vulnerabilities under different conditions. While several investigations have been published evaluating covert channel potential in infrastructure- and manufacturing-based contexts, no existing research explores Precision Time Protocol (PTP), a time synchronization protocol commonly used in industrial control systems. This study aims to fill this gap by demonstrating the feasibility of a covert channel-based attack on a PTP-enabled network.

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 …

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 …

Faster Multidimensional Data Queries On Infrastructure Monitoring Systems, Yinghua Qin, Gheorghi Guzun

Faculty Research, Scholarly, and Creative Activity

The analytics in online performance monitoring systems have often been limited due to the query performance of large scale multidimensional data. In this paper, we introduce a faster query approach using the bit-sliced index (BSI). Our study covers multidimensional grouping and preference top-k queries with the BSI, algorithms design, time complexity evaluation, and the query time comparison on a real-time production performance monitoring system. Our research work extended the BSI algorithms to cover attributes filtering and multidimensional grouping. We evaluated the query time with the single attribute, multiple attributes, feature filtering, and multidimensional grouping. To compare with the existing prior …

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 …