Physical Sciences and Mathematics Commons^™

Qasm-To-Hls: A Framework For Accelerating Quantum Circuit Emulation On High-Performance Reconfigurable Computers, Anshul Maurya

Theses and Dissertations

High-performance reconfigurable computers (HPRCs) make use of Field-Programmable Gate Arrays (FPGAs) for efficient emulation of quantum algorithms. Generally, algorithm-specific architectures are implemented on the FPGAs and there is very little flexibility. Moreover, mapping a quantum algorithm onto its equivalent FPGA emulation architecture is challenging. In this work, we present an automation framework for converting quantum circuits to their equivalent FPGA emulation architectures. The framework processes quantum circuits represented in Quantum Assembly Language (QASM) and derives high-level descriptions of the hardware emulation architectures for High-Level Synthesis (HLS) on HPRCs. The framework generates the code for a heterogeneous architecture consisting of a …

Accelerating Machine Learning Inference For Satellite Component Feature Extraction Using Fpgas., Andrew Ekblad

Theses and Dissertations

Running computer vision algorithms requires complex devices with lots of computing power, these types of devices are not well suited for space deployment. The harsh radiation environment and limited power budgets have hindered the ability of running advanced computer vision algorithms in space. This problem makes running an on-orbit servicing detection algorithm very difficult. This work proposes using a low powered FPGA to accelerate the computer vision algorithms that enable satellite component feature extraction. This work uses AMD/Xilinx’s Zynq SoC and DPU IP to run model inference. Experiments in this work centered around improving model post processing by creating implementations …

Secure And Efficient Federated Learning, Xingyu Li

Theses and Dissertations

In the past 10 years, the growth of machine learning technology has been significant, largely due to the availability of large datasets for training. However, gathering a sufficient amount of data on a central server can be challenging. Additionally, with the rise of mobile networking and the large amounts of data generated by IoT devices, privacy and security issues have become a concern, resulting in government regulations such as GDPR, HIPAA, CCPA, and ADPPA. Under these circumstances, traditional centralized machine learning methods face a problem in that sensitive data must be kept locally for privacy reasons, making it difficult to …

Exploiting The Iot Through Network-Based Covert Channels, Kyle S. Harris

Theses and Dissertations

Information leaks are a top concern to industry and government leaders. The IoT is a technology capable of sensing real-world events. A method for exfiltrating data from these devices is by covert channel. This research designs a novel IoT CTC without the need for inter-packet delays to encode data. Instead, it encodes data within preexisting network information, namely ports or addresses. Additionally, the CTC can be implemented in two different modes: Stealth and Bandwidth. Performance is measured using throughput and detectability. The Stealth methods mimic legitimate traffic captures while the Bandwidth methods forgo this approach for maximum throughput. Detection results …

Securing Infiniband Networks With End-Point Encryption, Noah B. Diamond

Theses and Dissertations

The NVIDIA-Mellanox Bluefield-2 is a 100 Gbps high-performance network interface which offers hardware offload and acceleration features that can operate directly on network traffic without routine involvement from the ARM CPU. This allows the ARM multi-core CPU to orchestrate the hardware to perform operations on both Ethernet and RDMA traffic at high rates rather than processing all the traffic directly. A testbed called TNAP was created for performance testing and a MiTM verification process called MiTMVMP is used to ensure proper network configuration. The hardware accelerators of the Bluefield-2 support a throughput of nearly 86 Gbps when using IPsec to …

Learning Robot Motion From Creative Human Demonstration, Charles C. Dietzel

Theses and Dissertations

This thesis presents a learning from demonstration framework that enables a robot to learn and perform creative motions from human demonstrations in real-time. In order to satisfy all of the functional requirements for the framework, the developed technique is comprised of two modular components, which integrate together to provide the desired functionality. The first component, called Dancing from Demonstration (DfD), is a kinesthetic learning from demonstration technique. This technique is capable of playing back newly learned motions in real-time, as well as combining multiple learned motions together in a configurable way, either to reduce trajectory error or to generate entirely …

Rebalancing Shared Mobility Systems By User Incentive Scheme Via Reinforcement Learning, Matthew Brian Schofield

Theses and Dissertations

Shared mobility systems regularly suffer from an imbalance of vehicle supply within the system, leading to users being unable to receive service. If such imbalance problems are not mitigated some users will not be serviced. There is an increasing interest in the use of reinforcement learning (RL) techniques for improving the resource supply balance and service level of systems. The goal of these techniques is to produce an effective user incentivization policy scheme to encourage users of a shared mobility system to slightly alter their travel behavior in exchange for a small monetary incentive. These slight changes in user behavior …

Stock Markets Performance During A Pandemic: How Contagious Is Covid-19?, Yara Abushahba

Theses and Dissertations

Background and Motivation: The coronavirus (“COVID-19”) pandemic, the subsequent policies and lockdowns have unarguably led to an unprecedented fluid circumstance worldwide. The panic and fluctuations in the stock markets were unparalleled. It is inarguable that real-time availability of news and social media platforms like Twitter played a vital role in driving the investors’ sentiment during such global shock.

Purpose:The purpose of this thesis is to study how the investor sentiment in relation to COVID-19 pandemic influenced stock markets globally and how stock markets globally are integrated and contagious. We analyze COVID-19 sentiment through the Twitter posts and investigate its …

Infiniband Network Monitoring: Challenges And Possibilities, Kyle D. Hintze

Theses and Dissertations

Within the realm of High Performance Computing, the InfiniBand Architecture is among the leading interconnects used today. Capable of providing high bandwidth and low latency, InfiniBand is finding applications outside the High Performance Computing domain. One of these is critical infrastructure, encompassing almost all essential sectors as the work force becomes more connected. InfiniBand is not immune to security risks, as prior research has shown that common traffic analyzing tools cannot effectively monitor InfiniBand traffic transmitted between hosts, due to the kernel bypass nature of the IBA in conjunction with Remote Direct Memory Access operations. If Remote Direct Memory Access …

Automated Network Exploitation Utilizing Bayesian Decision Networks, Graeme M. Roberts

Theses and Dissertations

Computer Network Exploitation (CNE) is the process of using tactics and techniques to penetrate computer systems and networks in order to achieve desired effects. It is currently a manual process requiring significant experience and time that are in limited supply. This thesis presents the Automated Network Discovery and Exploitation System (ANDES) which demonstrates that it is feasible to automate the CNE process. The uniqueness of ANDES is the use of Bayesian decision networks to represent the CNE domain and subject matter expert knowledge. ANDES conducts multiple execution cycles, which build upon previous action results. Cycles begin by modeling the current …

Exploring Fog Of War Concepts In Wargame Scenarios, Dillon N. Tryhorn

Theses and Dissertations

This thesis explores fog of war concepts through three submitted journal articles. The Department of Defense and U.S. Air Force are attempting to analyze war scenarios to aid the decision-making process; fog modeling improves realism in these wargame scenarios. The first article "Navigating an Enemy Contested Area with a Parallel Search Algorithm" [1] investigates a parallel algorithm's speedup, compared to the sequential implementation, with varying map configurations in a tile-based wargame. The parallel speedup tends to exceed 50 but in certain situations. The sequential algorithm outperforms it depending on the configuration of enemy location and amount on the map. The …

Enumerating And Locating Bluetooth Devices For Casualty Recovery In A First-Responder Environment, Justin M. Durham

Theses and Dissertations

It is difficult for first-responders to quickly locate casualties in an emergency environment such as an explosion or natural disaster. In order to provide another tool to locate individuals, this research attempts to identify and estimate the location of devices that would likely be located on or with a person. A variety of devices, such as phones, smartwatches, and Bluetooth-enabled locks, are tested in multiple environments and at various heights to determine the impact that placement and interference played in locating the devices. The hypothesis is that most Bluetooth devices can be successfully enumerated quickly, but cannot be accurately located …

Remote Monitoring Of Memory Data Structures For Malware Detection In A Talos Ii Architecture, Robert A. Willburn

Theses and Dissertations

New forms of malware, namely xC;leless malware and rootkits, pose a threat to traditional anti-malware. In particular, Rootkits have the capacity to obscure the present state of memory from the user space of a target machine. If thishappens, anti-malware running in the user space of an axB;ected machine cannot be trusted to operate properly. To combat this threat, this research proposes the remote monitoring of memory from a second, secure processor runningOpenBMC, serving as a baseboard management controller for a POWER9 processor, which is assumed vulnerable to exploitation. The baseboard management controller includes an application called pdbg, used for debugging …

Long Distance Bluetooth Low Energy Exploitation On A Wireless Attack Platform, Stephanie L. Long

Theses and Dissertations

In the past decade, embedded technology, known as the Internet of Things, has expanded for many uses. The smart home infrastructure has drastically grown to include networked refrigerators, lighting systems, speakers, watches, and more. This increase in the use of wireless protocols provides a larger attack surface for cyber actors than ever before. Wireless loT traffic is susceptible for sniffing by an attacker. The attack platform skypie is upgraded to incorporate Bluetooth Low Energy (BLE) beacon collection for pattern-of-life data, as well as device characteristic enumeration and potential characteristic modification. This platform allows an attacker to mount the skypie to …

Direct Digital Synthesis: A Flexible Architecture For Advanced Signals Research For Future Satellite Navigation Payloads, Pranav R. Patel

Theses and Dissertations

In legacy Global Positioning System (GPS) Satellite Navigation (SatNav) payloads, the architecture does not provide the flexibility to adapt to changing circumstances and environments. GPS SatNav payloads have largely remained unchanged since the system became fully operational in April 1995. Since then, the use of GPS has become ubiquitous in our day-to-day lives. GPS availability is now a basic assumption for distributed infrastructure; it has become inextricably tied to our national power grids, cellular networks, and global financial systems. Emerging advancements of easy to use radio technologies, such as software-defined radios (SDRs), have greatly lowered the difficulty of discovery and …

Joint 1d And 2d Neural Networks For Automatic Modulation Recognition, Luis M. Rosario Morel

Theses and Dissertations

The digital communication and radar community has recently manifested more interest in using data-driven approaches for tasks such as modulation recognition, channel estimation and distortion correction. In this research we seek to apply an object detector for parameter estimation to perform waveform separation in the time and frequency domain prior to classification. This enables the full automation of detecting and classifying simultaneously occurring waveforms. We leverage a lD ResNet implemented by O'Shea et al. in [1] and the YOLO v3 object detector designed by Redmon et al. in [2]. We conducted an in depth study of the performance of these …

An Overlay Architecture For Pattern Matching, Rasha Elham Karakchi

Theses and Dissertations

Deterministic and Non-deterministic Finite Automata (DFA and NFA) comprise the fundamental unit of work for many emerging big data applications, motivating recent efforts to develop Domain-Specific Architectures (DSAs) to exploit fine-grain parallelism available in automata workloads.

This dissertation presents NAPOLY (Non-Deterministic Automata Processor Over- LaY), an overlay architecture and associated software that attempt to maximally exploit on-chip memory parallelism for NFA evaluation. In order to avoid an upper bound in NFA size that commonly affects prior efforts, NAPOLY is optimized for runtime reconfiguration, allowing for full reconfiguration in 10s of microseconds. NAPOLY is also parameterizable, allowing for offline generation of …

A Machine Learning Based Approach To Accelerate Catalyst Discovery, Asif Jamil Chowdhury

Theses and Dissertations

Computational catalysis, in contrast to experimental catalysis, uses approximations such as density functional theory (DFT) to compute properties of reaction intermediates. But DFT calculations for a large number of surface species on variety of active site models are resource intensive. In this work, we are building a machine learning based predictive framework for adsorption energies of intermediate species, which can reduce the computational overhead significantly. Our work includes the study and development of appropriate machine learning models and effective fingerprints or descriptors to predict energies accurately for different scenarios. Furthermore, Bayesian inverse problem, that integrates experimental catalysis with its computational …

Sliver: Simulation-Based Logic Bomb Identification/Verification For Unmanned Aerial Vehicles, Jake M. Magness

Theses and Dissertations

This research introduces SLIVer, a Simulation-based Logic Bomb Identification/Verification methodology, for finding logic bombs hidden within Unmanned Aerial Vehicle (UAV) autopilot code without having access to the device source code. Effectiveness is demonstrated by executing a series of test missions within a high-fidelity software-in-the-loop (SITL) simulator. In the event that a logic bomb is not detected, this methodology defines safe operating areas for UAVs to ensure to a high degree of confidence the UAV operates normally on the defined flight plan. SLIVer uses preplanned flight paths as the baseline input space, greatly reducing the input space that must be searched …

Developing A Serious Game To Explore Joint All Domain Command And Control, Nathaniel W. Flack

Theses and Dissertations

Changes in the geopolitical landscape and increasing technological complexity have prompted the U.S. Military to coin Multi-Domain Operations (MDO) and Joint All-Domain Command and Control as terms to describe an over-arching strategy that frames the complexity of warfare across both traditional and emerging warfighting domains. Teaching new and advanced concepts associated with these terms requires both innovation as well as distinct education and training tools in order to realize the cultural change advocated by senior military leaders. BSN, a Collectible Card Game, was developed to teach concepts integral to MDO and initiate discussion on military strategy.

Interoperable Ads-B Confidentiality, Brandon C. Burfeind

Theses and Dissertations

The worldwide air traffic infrastructure is in the late stages of transition from legacy transponder systems to Automatic Dependent Surveillance - Broadcast (ADS-B) based systems. ADS-B relies on position information from GNSS and requires aircraft to transmit their identification, state, and position. ADS-B promises the availability of high-fidelity air traffic information; however, position and identification data are not secured via authentication or encryption. This lack of security for ADS-B allows non-participants to observe and collect data on both government and private flight activity. This is a proposal for a lightweight, interoperable ADS-B confidentiality protocol which uses existing format preserving encryption …

Leveraging Peer-To-Peer Energy Sharing For Resource Optimization In Mobile Social Networks, Aashish Dhungana

Theses and Dissertations

Mobile Opportunistic Networks (MSNs) enable the interaction of mobile users in the vicinity through various short-range wireless communication technologies (e.g., Bluetooth, WiFi) and let them discover and exchange information directly or in ad hoc manner. Despite their promise to enable many exciting applications, limited battery capacity of mobile devices has become the biggest impediment to these appli- cations. The recent breakthroughs in the areas of wireless power transfer (WPT) and rechargeable lithium batteries promise the use of peer-to-peer (P2P) energy sharing (i.e., the transfer of energy from the battery of one member of the mobile network to the battery of …

The Trust-Based Interactive Partially Observable Markov Decision Process, Richard S. Seymour

Theses and Dissertations

Cooperative agent and robot systems are designed so that each is working toward the same common good. The problem is that the software systems are extremely complex and can be subverted by an adversary to either break the system or potentially worse, create sneaky agents who are willing to cooperate when the stakes are low and take selfish, greedy actions when the rewards rise. This research focuses on the ability of a group of agents to reason about the trustworthiness of each other and make decisions about whether to cooperate. A trust-based interactive partially observable Markov decision process (TI-POMDP) is …

Instantaneous Bandwidth Expansion Using Software Defined Radios, Nicholas D. Everett

Theses and Dissertations

The Stimulated Unintended Radiated Emissions (SURE) process has been proven capable of classifying a device (e.g. a loaded antenna) as either operational or defective. Currently, the SURE process utilizes a specialized noise radar which is bulky, expensive and not easily supported. With current technology advancements, Software Defined Radios (SDRs) have become more compact, more readily available and significantly cheaper. The research here examines whether multiple SDRs can be integrated to replace the current specialized ultra-wideband noise radar used with the SURE process. The research specifically targets whether or not multiple SDR sub-band collections can be combined to form a wider …

Confidence Inference In Defensive Cyber Operator Decision Making, Graig S. Ganitano

Theses and Dissertations

Cyber defense analysts face the challenge of validating machine generated alerts regarding network-based security threats. Operations tempo and systematic manpower issues have increased the importance of these individual analyst decisions, since they typically are not reviewed or changed. Analysts may not always be confident in their decisions. If confidence can be accurately assessed, then analyst decisions made under low confidence can be independently reviewed and analysts can be offered decision assistance or additional training. This work investigates the utility of using neurophysiological and behavioral correlates of decision confidence to train machine learning models to infer confidence in analyst decisions. Electroencephalography …

Near Real-Time Rf-Dna Fingerprinting For Zigbee Devices Using Software Defined Radios, Frankie A. Cruz

Theses and Dissertations

Low-Rate Wireless Personal Area Network(s) (LR-WPAN) usage has increased as more consumers embrace Internet of Things (IoT) devices. ZigBee Physical Layer (PHY) is based on the Institute of Electrical and Electronics Engineers (IEEE) 802.15.4 specification designed to provide a low-cost, low-power, and low-complexity solution for Wireless Sensor Network(s) (WSN). The standard’s extended battery life and reliability makes ZigBee WSN a popular choice for home automation, transportation, traffic management, Industrial Control Systems (ICS), and cyber-physical systems. As robust and versatile as the standard is, ZigBee remains vulnerable to a myriad of common network attacks. Previous research involving Radio Frequency-Distinct Native Attribute …

A Blockchain-Based Anomalous Detection System For Internet Of Things Devices, Joshua K. Mosby

Theses and Dissertations

Internet of Things devices are highly susceptible to attack, and owners often fail to realize they have been compromised. This thesis describes an anomalous-based intrusion detection system that operates directly on Internet of Things devices utilizing a custom-built Blockchain. In this approach, an agent on each node compares the node's behavior to that of its peers, generating an alert if they are behaving differently. An experiment is conducted to determine the effectiveness at detecting malware. Three different code samples simulating common malware are deployed against a testbed of 12 Raspberry Pi devices. Increasing numbers are infected until two-thirds of the …

Infrared And Electro-Optical Stereo Vision For Automated Aerial Refueling, William E. Dallmann

Theses and Dissertations

Currently, Unmanned Aerial Vehicles are unsafe to refuel in-flight due to the communication latency between the UAVs ground operator and the UAV. Providing UAVs with an in-flight refueling capability would improve their functionality by extending their flight duration and increasing their flight payload. Our solution to this problem is Automated Aerial Refueling (AAR) using stereo vision from stereo electro-optical and infrared cameras on a refueling tanker. To simulate a refueling scenario, we use ground vehicles to simulate a pseudo tanker and pseudo receiver UAV. Imagery of the receiver is collected by the cameras on the tanker and processed by a …

The Use Of Recommender Systems In Web Applications – The Troi Case, Donjeta Mulaj

Theses and Dissertations

Avoiding digital marketing, surveys, reviews and online users behavior approaches on digital age are the key elements for a powerful businesses to fail, there are some systems that should preceded some artificial intelligence techniques. In this direction, the use of data mining for recommending relevant items as a new state of the art technique is increasing user satisfaction as well as the business revenues. And other related information gathering approaches in order to our systems thing and acts like humans. To do so there is a Recommender System that will be elaborated in this thesis. How people interact, how to …

Performanca E Makinave Kerkuese Duke Perdorur Cloud Shërbimet “Elasticsearch” Dhe “Algolia”, Besnik Korça

Theses and Dissertations

Ueb Aplikacionet me data-set të mëdha në kohën e tanishme janë shumë më të përhapura. Kërkimet e të dhënave në data-set të tilla për shkak të performances bëhen duke përdorur makinat kërkuese. Provider të ndryshëm ofrojnë makina kërkuese si Software as a Service(SaaS) shërbime të cilat kanë për avantazh konfigurimin minimal që duhet bërë makinave kërkuese për t’i vënë në funksion. Nëpërmjet këtij punimi synohet që së pari të analizohen shërbimet cloud computing që ofrohen nga provider të ndryshem. Pastaj pasi që fokusi i makinave kërkuese ndodhet në “information retrieval” është bë analizimi i disa teknikave të “information retrieval”. Makinat …