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Articles 1 - 20 of 20
Full-Text Articles in Engineering
Adaptive-Hybrid Redundancy For Radiation Hardening, Nicolas S. Hamilton
Adaptive-Hybrid Redundancy For Radiation Hardening, Nicolas S. Hamilton
Theses and Dissertations
An Adaptive-Hybrid Redundancy (AHR) mitigation strategy is proposed to mitigate the effects of Single Event Upset (SEU) and Single Event Transient (SET) radiation effects. AHR is adaptive because it switches between Triple Modular Redundancy (TMR) and Temporal Software Redundancy (TSR). AHR is hybrid because it uses hardware and software redundancy. AHR is demonstrated to run faster than TSR and use less energy than TMR. Furthermore, AHR allows space vehicle designers, mission planners, and operators the flexibility to determine how much time is spent in TMR and TSR. TMR mode provides faster processing at the expense of greater energy usage. TSR …
The Trust-Based Interactive Partially Observable Markov Decision Process, Richard S. Seymour
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
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 …
Graph-Based Temporal Analysis In Digital Forensics, Nikolai A. Adderley
Graph-Based Temporal Analysis In Digital Forensics, Nikolai A. Adderley
Theses and Dissertations
Establishing a timeline as part of a digital forensics investigation is a vital part of understanding the order in which system events occurred. However, most digital forensics tools present timelines as histogram or as raw artifacts. Consequently, digital forensics examiners are forced to rely on manual, labor-intensive practices to reconstruct system events. Current digital forensics analysis tools are at their technological limit with the increasing storage and complexity of data. A graph-based timeline can present digital forensics evidence in a structure that can be immediately understood and effortlessly focused. This paper presents the Temporal Analysis Integration Management Application (TAIMA) to …
Machine Learning Models Of C-17 Specific Range Using Flight Recorder Data, Marcus Catchpole
Machine Learning Models Of C-17 Specific Range Using Flight Recorder Data, Marcus Catchpole
Theses and Dissertations
Fuel is a significant expense for the Air Force. The C-17 Globemaster eet accounts for a significant portion. Estimating the range of an aircraft based on its fuel consumption is nearly as old as flight itself. Consideration of operational energy and the related consideration of fuel efficiency is increasing. Meanwhile machine learning and data-mining techniques are on the rise. The old question, "How far can my aircraft y with a given load cargo and fuel?" has given way to "How little fuel can I load into an aircraft and safely arrive at the destination?" Specific range is a measure of …
Machine Translation With Image Context From Mandarin Chinese To English, Brooke E. Johnson
Machine Translation With Image Context From Mandarin Chinese To English, Brooke E. Johnson
Theses and Dissertations
Despite ongoing improvements in machine translation, machine translators still lack the capability of incorporating context from which source text may have been derived. Machine translators use text from a source language to translate it into a target language without observing any visual context. This work aims to produce a neural machine translation model that is capable of accepting both text and image context as a multimodal translator from Mandarin Chinese to English. The model was trained on a small multimodal dataset of 700 images and sentences, and compared to a translator trained only on the text associated with those images. …
Examining Effectiveness Of Web-Based Internet Of Things Honeypots, Lukas A. Stafira
Examining Effectiveness Of Web-Based Internet Of Things Honeypots, Lukas A. Stafira
Theses and Dissertations
The Internet of Things (IoT) is growing at an alarming rate. It is estimated that there will be over 25 billion IoT devices by 2020. The simplicity of their function usually means that IoT devices have low processing power, which prevent them from having intricate security features, leading to vulnerabilities. This makes IoT devices the prime target of attackers in the coming years. Honeypots are intentionally vulnerable machines that run programs which appear as a vulnerable device to a would-be attacker. They are placed on a network to entice and trap an attacker and then gather information on them, including …
Confidence Inference In Defensive Cyber Operator Decision Making, Graig S. Ganitano
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 …
A Quantitative Analysis Of The Fusion Of 3-D Scanning Lidar Systems And 2-D Imaging Systems, Michael F. Milton Jr.
A Quantitative Analysis Of The Fusion Of 3-D Scanning Lidar Systems And 2-D Imaging Systems, Michael F. Milton Jr.
Theses and Dissertations
This research will demonstrate the feasibility of fusing the superior spatial resolution of a 2-D imaging system with the precise range to target information of a 3-D imaging system to create a LIDAR imaging system that can accurately find what and where a target is. The 3-D imaging system will use a scanning method as opposed to a flash method that has been used in similar research. The goal of this research is to improve performance of scanning LIDAR so it has better spatial resolution. The research in this thesis proves that incorporating 2-D imaging data into 3-D scanning LIDAR …
High Resolution Low-Bandwidth Real-Time Reconnaissance Using Structure From Motion With Planar Homography Estimation, Christian M.A. Arnold
High Resolution Low-Bandwidth Real-Time Reconnaissance Using Structure From Motion With Planar Homography Estimation, Christian M.A. Arnold
Theses and Dissertations
Aerial real-time surveillance exists in a paradigm balancing the constraints of delivering high quality data and transporting data quickly. Typically, to have more of one, sacrifices must be made to the other. This is true of the environment in which an Unmanned Aerial Vehicle (UAV) operates, where real-time communication may be done through a low-bandwidth satellite connection resulting in low-resolution data, and serves as the primary limiting factor in all intelligence operations. Through the use of efficient computer vision techniques, we propose a new Structure from Motion (SfM) method capable of compressing high-resolution data, and delivering that data in real-time. …
Modeling A Consortium-Based Distributed Ledger Network With Applications For Intelligent Transportation Infrastructure, Luis A. Cintron
Modeling A Consortium-Based Distributed Ledger Network With Applications For Intelligent Transportation Infrastructure, Luis A. Cintron
Theses and Dissertations
Emerging distributed-ledger networks are changing the landscape for environments of low trust among participating entities. Implementing such technologies in transportation infrastructure communications and operations would enable, in a secure fashion, decentralized collaboration among entities who do not fully trust each other. This work models a transportation records and events data collection system enabled by a Hyperledger Fabric blockchain network and simulated using a transportation environment modeling tool. A distributed vehicle records management use case is shown with the capability to detect and prevent unauthorized vehicle odometer tampering. Another use case studied is that of vehicular data collected during the event …
Near Real-Time Rf-Dna Fingerprinting For Zigbee Devices Using Software Defined Radios, Frankie A. Cruz
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 Multi-Vehicle Cooperative Localization Approach For An Autonomy Framework, Edwin A. Mora
A Multi-Vehicle Cooperative Localization Approach For An Autonomy Framework, Edwin A. Mora
Theses and Dissertations
Offensive techniques produced by technological advancement present opportunities for adversaries to threaten the operational advantages of our joint and allied forces. Combating these new methodologies requires continuous and rapid development towards our own set of \game-changing" technologies. Through focused development of unmanned systems and autonomy, the Air Force can strive to maintain its technological superiority. Furthermore, creating a robust framework capable of testing and evaluating the principles that define autonomy allows for the exploration of future capabilities. This research presents development towards a hybrid reactive/deliberative architecture that will allow for the testing of the principles of task, cognitive, and peer …
A Blockchain-Based Anomalous Detection System For Internet Of Things Devices, Joshua K. Mosby
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 …
A Framework For Cyber Vulnerability Assessments Of Infiniband Networks, Daryl W. Schmitt
A Framework For Cyber Vulnerability Assessments Of Infiniband Networks, Daryl W. Schmitt
Theses and Dissertations
InfiniBand is a popular Input/Output interconnect technology used in High Performance Computing clusters. It is employed in over a quarter of the world’s 500 fastest computer systems. Although it was created to provide extremely low network latency with a high Quality of Service, the cybersecurity aspects of InfiniBand have yet to be thoroughly investigated. The InfiniBand Architecture was designed as a data center technology, logically separated from the Internet, so defensive mechanisms such as packet encryption were not implemented. Cyber communities do not appear to have taken an interest in InfiniBand, but that is likely to change as attackers branch …
Autonomous Association Of Geo Rso Observations Using Deep Neural Networks, Ian W. Mcquaid
Autonomous Association Of Geo Rso Observations Using Deep Neural Networks, Ian W. Mcquaid
Theses and Dissertations
Ground-based non-resolved optical observations of resident space objects (RSOs) in geosynchronous orbit (GEO) represent the majority of the space surveillance network’s (SSN’s) deep-space tracking. Reliable and accurate tracking necessitates temporal separation of the observations. This requires that subsequent observations be associated with prior observations of a given RSO before they can be used to create or refine that RSO’s ephemeris. The use of astrometric data (e.g. topocentric angular position) alone for this association task is complicated by RSO maneuvers between observations, and by RSOs operating in close proximity. Accurately associating an observation with an RSO thus motivates the use of …
Unresolved Object Detection Using Synthetic Data Generation And Artificial Neural Networks, Yong U. Sinn
Unresolved Object Detection Using Synthetic Data Generation And Artificial Neural Networks, Yong U. Sinn
Theses and Dissertations
This research presents and solves constrained real-world problems of using synthetic data to train artificial neural networks (ANNs) to detect unresolved moving objects in wide field of view (WFOV) electro-optical/infrared (EO/IR) satellite motion imagery. Objectives include demonstrating the use of the Air Force Institute of Technology (AFIT) Sensor and Scene Emulation Tool (ASSET) as an effective tool for generating EO/IR motion imagery representative of real WFOV sensors and describing the ANN architectures, training, and testing results obtained. Deep learning using a 3-D convolutional neural network (3D ConvNet), long short term memory (LSTM) network, and U-Net are used to solve the …
Hyper-Parameter Optimization Of A Convolutional Neural Network, Steven H. Chon
Hyper-Parameter Optimization Of A Convolutional Neural Network, Steven H. Chon
Theses and Dissertations
In the world of machine learning, neural networks have become a powerful pattern recognition technique that gives a user the ability to interpret high-dimensional data whereas conventional methods, such as logistic regression, would fail. There exists many different types of neural networks, each containing its own set of hyper-parameters that are dependent on the type of analysis required, but the focus of this paper will be on the hyper-parameters of convolutional neural networks. Convolutional neural networks are commonly used for classifications of visual imagery. For example, if you were to build a network for the purpose of predicting a specific …
A Stochastic Game Theoretical Model For Cyber Security, Michael T. Larkin
A Stochastic Game Theoretical Model For Cyber Security, Michael T. Larkin
Theses and Dissertations
The resiliency of systems integrated through cyber networks is of utmost importance due to the reliance on these systems for critical services such as industrial control systems, nuclear production, and military weapons systems. Current research in cyber resiliency remains largely limited to methodologies utilizing a singular technique that is predominantly theoretical with limited examples given. This research uses notional data in presenting a novel approach to cyber system analysis and network resource allocation by leveraging multiple techniques including game theory, stochastic processes, and mathematical programming. An operational network security problem consisting of 20 tactical normal form games provides an assessment …
Infrared And Electro-Optical Stereo Vision For Automated Aerial Refueling, William E. Dallmann
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 …