Digital Commons Network^™

Intel Total Memory Encryption: Functional Verification And Performance Analysis, Tallas T. S. Goo

Theses and Dissertations

While more attention is generally focused on software security, computer hardware security remains an important effort. Should an attacker gain direct physical access, computers with little to no hardware security can quickly be compromised via a manner of methods. One such attacker method is to steal information directly from the active memory of a locked, powered-on computer. To counter this attack, a hardware security method was developed called memory encryption. Memory encryption, as the name suggests, protects against adversary methods like cold boot attacks by encrypting all of memory. This research evaluates the efficacy and performance specifically of Intel TME. …

Characterizing Location-Based Electromagnetic Leakage Of Computing Devices Using Convolutional Neural Networks To Increase The Effectiveness Of Side-Channel Analysis Attacks, Ian C. Heffron

Theses and Dissertations

SCA attacks aim to recover some sort of secret information, often in the form of a cipher key, from a target device. Some of these attacks focus on either power-based leakage, or EM-based leakage. Neural networks have recently gained in popularity as tools in SCA attacks. Near-field EM probes with high-spatial resolution enable attackers to isolate physical locations above a processor. This enables attackers to exploit the spatial dependencies of algorithms running on said processor. These spatial dependencies result in different physical locations above a chip emanating different signal strengths. The strengths of different locations can be mapped using the …

Magnetic Anomaly Mapping For Navigation, Luke T. Bergeron

Theses and Dissertations

Magnetic navigation (MagNav) has the potential to provide a global form of navigation that uses magnetic measurements of the Earth’s anomaly magnetic field and compares those measurements to a magnetic anomaly map in order to determine the user’s position. Widespread use of MagNav will require a database of fully-sampled, low-altitude magnetic anomaly maps. Existing magnetic anomaly map databases usually come from under- or poorly-sampled surveys. In this work, we provide an easy to follow MagNav anomaly map generation framework and set of survey collection metrics/requirements in an effort to help facilitate and standardize the creation of such a database. We …

The Electromagnetic Bayonet: Development Of A Scientific Computing Method For Aperture Antenna Optimization, Michael P. Ingold

Theses and Dissertations

The quiet zone of a radar range is the region over which a transmitted EM field approximates a uniform plane wave to within some finite error tolerance. Any target to be measured must physically fit within this quiet zone to prevent excess measurement error. Compact radar ranges offer significant operational advantages for performing RCS measurements but their quiet zone sizes are constrained by space limitations. In this work, a scientific computing approach is used to investigate whether equivalent-current transmitters can be designed that generate larger quiet zones than a conventional version at short range. A time-domain near-field solver, JefimenkoModels, was …

Classification Tradeoffs In Multispectral Polarimetric Ladar Architectures, Connor B. Martin

Theses and Dissertations

An end-to-end LADAR system is modeled at the waveform level to perform material classification at a per-pixel basis. A K-Nearest Neighbors machine learning algorithm is chosen to make predictions using polarimetric material characteristics as features. A variable receiver design is modeled to allow for the use of multiple configurations of Polarization State Analyzers. This research investigates the inclusion of multiple wavelengths in the transmitted laser pulse to improve classification accuracy. Additionally, the effects of lowering the receiver’s detector bandwidth are investigated. Through the classification process, transmitting a multispectral laser pulse is shown to improve classification and may improve future LADAR …

Belief Space Planning For Alternative Navigation In Gnss-Denied Environments, Timothy I. Machin

Theses and Dissertations

Robust alternative navigation for autonomous agents becomes critical without reliable GNSS. Autonomous agents utilize measurement updates to constrain uncertainty. Belief space planning builds graph structures of beliefs within environments based on probable paths, agent and measurement models, and information of the environment. The Rapidly-exploring Random Alt-Nav Belief Graph (RRBANG) algorithm leverages stochastic filtering to implement a range of alt-nav measurement capabilities for robust navigation in GNSS-denied environments.

Effects Of Calibration Errors On Dropped-Channel Polarimetric Synthetic Aperture Radar, Jacob C. Morrison

Theses and Dissertations

Compressed Sensing (CS) is a mathematical technique that can be applied to sparse data sets to allow for sub-Nyquist sampling. DCPCS is a CS technique that recovers the signal from unmeasured polarisation channels due to antenna crosstalk coupling the information onto the remaining channels. DCPCS reduces data storage/transmission and receiver hardware requirements. This thesis examines the robustness of DCPCS to calibration errors on the antenna crosstalk matrix. Although the antenna design problem is relaxed to a large region of acceptable crosstalk values, very accurate calibration may be required in a monostatic radar. This thesis also looks at the importance of …

Modeling The Effects Of Radiation On Microelectromechanical Resonators, David D. Lynes

Theses and Dissertations

As the use of MEMS becomes more prolific in air, space, defense, and power applications, they will be exposed to more extreme radiation environments. This dissertation explores the effects of ionizing and nonionizing radiation on MEMS. AlN-on-Si based piezoelectric bulk acoustic wave resonators were irradiated by gamma-rays and silicon ions while measuring S-parameters in situ. Changes to the resonator and equivalent circuit parameters are extracted. The resonators demonstrated resilience against the effects of radiation-induced charge trapping. However, radiation-induced atomic displacements caused shifts to resonant frequency. From these data, an atomistic model is derived to describe the relationship between radiation type …

Fast And Accurate 3d Object Reconstruction For Cargo Load Planning, Adam R. Nasi

Theses and Dissertations

Cargo load planning involves efficiently packing objects into aircraft subject to constraints such as space and weight distribution. Currently, this is performed manually by loadmasters. The United States Air Force is investigating ways to automate this process in order to improve airlift operational readiness while saving money. The first step in such a process would be generating 3D reconstructions of cargo objects to be used by a load planning algorithm. To that end, this thesis presents a novel method for fast, scaled, and accurate 3D reconstruction of cargo objects. This method can scan a 2.5m×3m×2m object in less than 10 …

Robust Feature Matching For Visual-Based Aerial Navigation Using Registered Imagery, Luis Montenegro

Theses and Dissertations

This work leverages the SIFT detector along with known robust feature matching techniques for vision-aided sUAS navigation solutions. The proposed algorithm focuses on a sufficient number of features extracted, their quality and their distribution.

Ensemble Aggregation In A Multi-Perspective Environment, Jonathan P. Nash

Theses and Dissertations

Research towards improving the performance of artificial intelligence networks has found that larger and more complex networks tends to yield better results, and continuous hardware upgrades enables the development of larger, more complicated, and better performing neural networks. However, many devices that are widely available and more practical to everyday use, such as drones or smartphones, are unable to use the state-of-the-art neural networks because they simply do not have the processing capabilities to run them in addition to their normal function. It is possible to overcome this lower performance by using a variety of these smaller neural networks as …

Classifying Open-Air Target Measurements Using Simulation-Trained Convolutional Neural Networks, Matthew M. Rofrano

Theses and Dissertations

This research focuses on the development of machine learning networks that can identify and classify airborne targets using their radar cross section response. Simulation and measurement data for five targets was collected using Altair's CadFEKO software, and the Air Force Institute's Compact Radar Range. Three machine learning models were trained using simulation data, and evaluated using the collected measurement data. Variability is introduced to the training data by applying random gaussian noise to simulation results. Gaussian noise is added to the measurement data prior to evaluation in-order to model "hostile noise jamming." Network performance is measured against a baseline performance …

Adaptation Of Network Flow Problems For Course Of Action Generation, Alexander N. Stephens

Theses and Dissertations

This thesis introduces two methods to generate Courses of Action (COA) in distributed warfare scenarios: the Wargaming Commodity Course of Action Automated Method Under Uncertainty (WCCAAM-U2) and Dynamic Transshipment Problem (DTP)-generated COAs. Previous work by Deberry et al. used a Multi-Commodity Flow Problem (MCFP) to generate COAs for single-period wargame scenarios with known enemy force amounts. In WCCAAM-U2, we adapt an MCFP to work in situations where only intelligence estimates of enemy forces are known. Compared to two other COA-generation methods, the WCCAAAM-U2 COA outperforms the next highest-performing COA by 307% when compared by a ratio of objective success rate …

Spectral Material Classification Of Orbital Objects - Applying Machine Learning To Visible And Near-Infrared Spectral Scenes, Stephen M. Stumpf

Theses and Dissertations

MSI and HSI techniques allow users to determine the material composition of an object at range. To avoid labor-intensive manual classification, ML is used to determine the most likely material contained in a given pixel of a target image. Previous work primarily focuses on terrestrial applications; this paper extends these techniques into the low-illumination space situational awareness domain, which is of critical importance to national security. HSI datacubes are preprocessed with RL deconvolution as a means of reducing the effects of the optical PSF; then, statistical ML techniques, including k-NN, LDA, QDA, and SVMs are implemented as means of assigning …

Comparison Of Federated Kalman Filter And Autonomous Resilient Management Of All-Source Sensors (Armas) Framework For Fault Detection And Exclusion, Flavio Fernandes

Theses and Dissertations

In recent times, there is a great demand for resilient and robust PNT solutions. Current navigation systems rely heavily on GNSS to provide this solution. This dependence is a major concern and therefore it is prudent to use additional aids to provide the best solution possible. However, traditional methods to address this need require a nontrivial number of Kalman filters to maintain a fault-free solution. The federated filter approach provides an attractive alternative to the current solutions. In this thesis, we examine the use of the federated filter design to address this need in today’s integrated navigation systems. We compared …

Detection Algorithms And Clutter Metrics Comparison For Long Wave Infrared Point-Source Targets, Rudolf N. Vonniederhausern

Theses and Dissertations

In Infrared Search and Track (IRST) systems, clutter in the image hinders target detection especially in point-source target scenarios. Currently there is not a standardized metric for quantifying background clutter. Many clutter metrics have been proposed, but none have demonstrated effectiveness or compatibility for point-source targets. Factors such as environment conditions, detection algorithm, and correlation coefficient to probability of detection (PD) and false alarm (PFA) are the main considerations in determining the effectiveness of clutter metrics. Determining the most successful metric will increase Air Force Test and Evaluation (T&E) units’ capability by providing additional information on test conditions and environments …

Monocular Vision And Machine Learning For Pose Estimation, Quang Ngoc Tran

Theses and Dissertations

This thesis introduces a monocular vision-based approach for 6 DoF pose estimation on a known object. The proposed solution is to use a CNN to find known features of an object in an image. These known features, together with their known locations, are used by a PnP algorithm to estimate the pose of the target object with respect to the camera. The primary difficulty with CNN-based methods is needing to generate a large amount of training data to effectively create the CNN. To overcome this difficulty, a 3D model of the real-world object is created and used in a visualization …

Effectiveness Of A Timing Side Channel For Deriving Neural Network Depth, Matthew P. Weeks

Theses and Dissertations

From facial recognition on cell phones to vehicle traffic modeling for city planning, integrating ML models can be an expensive investment in resources. Protecting that investment is difficult, as information about the model and how it was built can be leaked through multiple channels, such as timing and memory access. In this thesis, one method of extracting data through a timing side-channel is examined across multiple hardware and software configurations to determine its reliability for general use. While attempting to determine the layer count of a target model solely from its inference time, the research determined that it is not …

Detection And Identification Of Covert Devices Using Infrared And Stacked Optics Detection, Michael A. Reyneke

Theses and Dissertations

This work investigates stacked optics detection methodologies to successfully detect and identify observational systems with a cyber-physical sensing tool, ODIN (Observational Device Identification Network). ODIN successfully detected the presence of stacked optics and LiDAR systems using night-vision devices with a 96.32% average accuracy rating, both overt and covertly placed, with objective lens diameters ranging from 17 mm to 50 mm at distances between 1 m to 5 m with and without commonly employed anti-reflective countermeasures. ODIN provides a foundation for counter- measure capabilities of NIR devices and stacked optical systems in stationary environments. Additionally, a pilot study on smartphone LiDAR …

Safe And Reliable Software And The Formal Verification Of Prim's Algorithm In Spark, Brian S. Wheelhouse

Theses and Dissertations

Despite evidence that formal verification helps produce highly reliable and secure code, formal methods, i.e., mathematically based tools and approaches for software and hardware verification, are not commonly used in software and hardware development. The limited emphasis on formal verification in software education and training suggests that many developers have never considered the benefits of formal verification. Despite the challenging nature of their mathematical roots, software verification tools have improved; making it easier than ever to verify software. SPARK, a programming language and a formal verification toolset, is of particular interest for the AFRL, and will be a primary focus …

Strategic Action Execution Through Regret Matching In Press Diplomacy, Leif D. White

Theses and Dissertations

To take most advantage of collaboration, negotiation is paramount to succeed in press Diplomacy. Humans use this construct to work towards self victory or sometimes towards an alternative strategic objective undefined in the game’s rules. To emulate this behavior, this thesis examines how to use communication to enable the victory or defeat of any other player in the game. This research develops a press Diplomacy agent, Lyre, that can work to attain these specific objectives in Diplomacy through the regret matching algorithm (RM). We also study how Lyre can begin Diplomacy with the goal to win, then shift strategies to …

Atmospheric Polarization And Solar Position As Kalman Updates To A Navigation Solution, Thomas J. Wheeler

Theses and Dissertations

Simulation and physical testing of a sensor that measures relative position of the Sun and polarization of light in the atmosphere as a navigational aid in a Kalman filter.

Temporal Convolutional Neural Networks For Device Discrimination, Ryan T. Zacher

Theses and Dissertations

This research uses TCN modifications to CNN classifiers, specifically dilation, causal padding, and residual blocks, to focus on temporal features and improve existing DNA analysis processes. Dilation significantly improves classification accuracy, even detecting features where no other models were able to. The smallest improvement shown is a 3-6dB reduction in SNR to reach a 90% classification accuracy. The maximum improvement is shown in the data-delivery region of the Cisco dataset, with the dilated model being the only model to exceed 90% classification accuracy. The other TCN modifications are shown to have no beneficial effect on the models.

Using Embedded Systems And Augmented Reality For Automated Aerial Refueling, Nathaniel A. Wilson

Theses and Dissertations

The goal of automated aerial refueling (AAR) is to extend the range of unmanned aircraft. Control latency prevents a human from remotely controlling the receiving aircraft as it approaches a tanker. To conform with the size, weight, and power constraints of a small unmanned aircraft, an AAR system must execute in real-time on an embedded platform. This thesis explores the timing and computational performance of a NVIDIA Jetson AGX Orin to a state-of-the-art general-purpose computer using existing AAR algorithms. It also constructs an augmented reality framework as an intermediate step for testing vision-based AAR algorithms between virtual testing and expensive …

Entering Hyperspace: Conditional Hyperspectral Reflectance Image Generation Using Convolutional Neural Networks, Bret M. Wagner

Theses and Dissertations

The field of remote sensing continues to expand in both commercial and defense domains. Development of advanced space based EOIR sensors has driven corresponding demand for sensor data for algorithm development. The AFIT Sensor and Scene Emulation Tool (ASSET) produces realistic synthetic electro-optical and infrared (EO/IR) data with absolute truth for the purpose of clutter suppression, target detection, and tracking algorithm development. This thesis presents a novel model which transforms panchromatic images into realistic hyperspectral reflectance images. The direct application of this model is to allows users to generate hyperspectral background images as inputs to ASSET allowing users to benefit …

Transition Analysis Of Innovative Technologies Into Military Applications, Cristian J. Henandez-Rivera

Theses and Dissertations

The Department of Defense (DoD) invests over 1 billion dollars annually in Small Business Innovation Research (SBIR) efforts. These SBIR efforts are similar to venture capital investments, where a transition beyond seed funding is considered a success. A baseline study of 2015-2018 Air Force SBIR investments indicates that 8.8% of the efforts secured long-term funding. Current data allows for an assessment of whether or not a project scores long-term funding; however, there is no measurement of whether or not the technology transitions to DoD usage. Transition is the rate at which SBIR investments are fielded or integrated into a military …

A Survey Of Barriers/Challenges To Improve Sbir Participation & Commercialization Success, Benjamin L. Berezin

Theses and Dissertations

The composition of the U.S. Defense Industrial Base (DIB) is changing. Within the last decade we have witnessed a decline in the percentage of new entrants, especially among Small Businesses. The Department of Defense’s base of small business participants experienced a drop of 23% from 2015-2021. New entrants provide novel capabilities and increase competition, spurring innovation essential for continued economic and military advantage. Small Businesses represent well over 40% of the Nation’s Gross Domestic Product and have vastly outpaced large firms at a magnitude of 16.5 times as many patents per small firm.

The Air Force deliberately targets funding for …

Protection Of Linear Assets In Arctic Regions Using Basic Expeditionary Airfield Resources (Polaar Bear), Christopher P. Lintz

Theses and Dissertations

In the 2018 United States National Defense Strategy, the Department of Defense mandated that forces are to be more dynamic and decentralized. The Arctic region was a key topic that was addressed. This means that in the future, it is possible that personnel will need to operate in the Arctic, away from the standard built up infrastructure, to enhance the capabilities of the Air Force and enable the power projection required for mission execution. When establishing a new location, water systems are one of the first requirements for setting up a temporary base infrastructure. However, the Air Force’s current expeditionary …

Topological Variability In Water Distribution Networks, James M. Anderson

Theses and Dissertations

Water distribution networks are critical infrastructure characterized by difficulties in their assessment and deteriorating performance due to aging components. Resilience analysis of networked infrastructure has replaced traditional risk analysis to focus on performance. Global Resilience Analysis can provide useful information to decision makers and system managers regarding repair and expansion of networks. Network performance has been found to be directly informed by network structure. This work leverages graph theory to assess network qualities that correlate with resiliency characteristics across 69 real world water networks. These networks are then grouped by their structural properties through k-means clustering and compared using parametric …

Environmental Trade-Offs Of Reverse Osmosis Water Purification Units (Rowpus) And Bottled Water, Caleb A. Boone

Theses and Dissertations

The Department of Defense (DoD) conducts many remote missions around the globe. As part of any remote basing strategy, potable water needs to be secured. Currently, there are three primary means of procuring potable water at remote locations: bottled water, on-site purification, or tie-in to existing, local infrastructure. The purpose of this study is to determine the environmental tradeoffs of bottled water and on-site treatment via a Reverse Osmosis Water Purification Unit (ROWPU), which uses multiple levels of filtration to make potable water from freshwater or saline water. A cradle-to- gate assessment was developed for both systems to create a …