Digital Commons Network^™

Improving Accessibility And Efficiency Of Analytic Provenance Tools For Reverse Engineering, Caleb W. Richardson

Theses and Dissertations

Reverse engineering is a vital technique for identifying and mitigating cyber threats. Yet, despite its importance, reverse engineering is a time-consuming process. Provenance tools help to improve the workflow of reverse engineers by providing an accessible method of viewing their flow through a binary. The current state-of-theart provenance tool for reverse engineering software called SensorRE, leverages an external server, web browser, and a large array of javascript libraries. This thesis presents Provenance Ninja, a software reverse engineering tool developed in Python that runs directly within Binary Ninja. Provenance Ninja captures reverse engineers’ provenance data and provides an interactive graph within …

Debris Survivability Study For Mega-Constellation Architectures, Joseph C. Canoy

Theses and Dissertations

The analysis for the overall theoretical debris survivabilty of mega-constellation architectures, with an emphasis on space-based ballistic missile defense constellation (SB-BMD), is explored via three extensive different Monte Carlo simulations: preliminary analysis of low Earth Orbit (LEO) mega-constellation survivabilty following a fragmentation event within the constellation, analysis of LEO mega-constellation survivability with a fragmentation event occurring on a satellite performing a maneuver to insert itself within the constellation, and the analysis of LEO mega-constellation survivabilty after a fragmentation event resulting from the destruction of a missile. The LEO mega-constellations represent the SB-BMD constellation. The first two analysis sections will include …

Direct Collocation Methods For Comparison Of Aerothermodynamic Models Effect On Hypersonic Trajectory Optimization By The Process Of Continuation, Noor K. Khan

Theses and Dissertations

An algorithm was created to optimize trajectories of hypersonic glide vehicles with selected cost functions by applying the process of continuation to direct orthogonal collocation methods. The trajectory was optimized to maximize the range of launch position given a fixed terminal location. The hypersonic glide vehicle system dynamics were modeled with three-dimensional, three degree of freedom equations of motion assuming no thrust and a non-rotating Earth with the control as bank angle. Three aerothermodynamic models were compared when input as path constraints to calculate the stagnation point heating rate at the nose as well as integrated for heat load. Use …

Optimal Gyroid Infill For Space Launch, Jose R. Lopez Cordell

Theses and Dissertations

This research characterizes the optimal gyroid infill design for the 1st frequency response of composite sandwich panels. Structural performance may be improved by designing the gyroid infill within the sandwich panel to have a 1st mode resonance frequency above typical launch vehicle vibrations. Ensuring a component generates a natural frequency response above a designed threshold is mandatory for space launch systems to prevent damage. The gyroid, a Triply Periodic Minimal Surface (TPMS), has the potential to provide close to isotropic stiffness in the principal axes with a minimal amount of material, making it an attractive choice for this application. This …

Critical Infrastructure System Resiliency Modeling Using Multi-Layer Network Optimization, Spencer R. Figge

Theses and Dissertations

ccurately modeling the interdependent operation of critical infrastructure systems is an effective and efficient way of proactively evaluating system vulnerabilities and resiliency. Infrastructure systems are designed to transport essential commodities from where they are produced to where they are consumed and network flow-based models are one of the most effective ways to simulate and quantify infrastructure performance. The literature is populated with proposed models that must balance accuracy of interdependent operations, capability to include real-world considerations, and computational cost. This research proposes an alternative network-flow based model called the Critical Infrastructure System Resiliency Model (CISRM) that focuses on modeling a …

Multicollinearity Applied Stepwise Stochastic Imputation: A Large Dataset Imputation Through Correlation‑Based Regression, Benjamin D. Leiby, Darryl K. Ahner

Faculty Publications

This paper presents a stochastic imputation approach for large datasets using a correlation selection methodology when preferred commercial packages struggle to iterate due to numerical problems. A variable range-based guard rail modification is proposed that benefits the convergence rate of data elements while simultaneously providing increased confidence in the plausibility of the imputations. A large country conflict dataset motivates the search to impute missing values well over a common threshold of 20% missingness. The Multicollinearity Applied Stepwise Stochastic imputation methodology (MASS-impute) capitalizes on correlation between variables within the dataset and uses model residuals to estimate unknown values. Examination of the …

Measurement Of Proton Light Yield Of Water-Based Liquid Scintillator, E. J. Callaghan, B. L. Goldblum, J. A. Brown, T. A. Laplace, Juan J. Manfredi, M. Yeh, G. D. Orebi Gann

Faculty Publications

The proton light yield of liquid scintillators is an important property in the context of their use in large-scale neutrino experiments, with direct implications for neutrino-proton scattering measurements and the discrimination of fast neutrons from inverse β-decay coincidence signals. This work presents the first measurement of the proton light yield of a water-based liquid scintillator (WbLS) formulated from 5% linear alkyl benzene (LAB), at energies below 20 MeV, as well as a measurement of the proton light yield of a pure LAB + 2 g/L 2,5-diphenyloxazole (PPO) mixture (LABPPO). The measurements were performed using a double time-of-flight method and a …

Emotion Classification Of Indonesian Tweets Using Bidirectional Lstm, Aaron K. Glenn, Phillip M. Lacasse, Bruce A. Cox

Faculty Publications

Emotion classification can be a powerful tool to derive narratives from social media data. Traditional machine learning models that perform emotion classification on Indonesian Twitter data exist but rely on closed-source features. Recurrent neural networks can meet or exceed the performance of state-of-the-art traditional machine learning techniques using exclusively open-source data and models. Specifically, these results show that recurrent neural network variants can produce more than an 8% gain in accuracy in comparison with logistic regression and SVM techniques and a 15% gain over random forest when using FastText embeddings. This research found a statistical significance in the performance of …

Data Augmentation For Neutron Spectrum Unfolding With Neural Networks, James Mcgreivy, Juan J. Manfredi, Daniel Siefman

Faculty Publications

Neural networks require a large quantity of training spectra and detector responses in order to learn to solve the inverse problem of neutron spectrum unfolding. In addition, due to the under-determined nature of unfolding, non-physical spectra which would not be encountered in usage should not be included in the training set. While physically realistic training spectra are commonly determined experimentally or generated through Monte Carlo simulation, this can become prohibitively expensive when considering the quantity of spectra needed to effectively train an unfolding network. In this paper, we present three algorithms for the generation of large quantities of realistic and …

Academic Year 2022-2023 Faculty Excellence Showcase, Afit Graduate School Of Engineering & Management, Graduate School Of Engineering And Management, Air Force Institute Of Technology

AFIT Documents

No abstract provided.

Fy2022 Annual Report Of The Graduate School Of Engineering And Management, Air Force Institute Of Technology, Office Of The Dean Of The Graduate School Of Engineering And Management, Air Force Institute Of Technology, Adedeji B. Badiru

AFIT Documents

The annual report is published each year by AFIT’s Office of the Dean, Graduate School of Engineering and Management at Wright-Patterson Air Force Base, Ohio. It shares information about the activities of the Graduate School with the U.S. Department of the Air Force (DAF), Department of Defense (DoD), and wider public.

Intentional Technology For Teaching Practice, Afit Faculty Learning Community, Mike Frick, Aaron V. Glassburner, Jose Gutierrez Del Arroyo, Rick Kappel, Rodney Mccoy, Jonathan Moore, Mark G. Reith, Timothy S. Wolfe, Jonathan Zemmer

AFIT Documents

In today’s era, where educational technology is in a near-constant state of evolution, the imperative is not just to adopt technology, but to do so with a defined purpose and strategy. As educators within military education there is a growing need to discern which technological tools and practices align best with our mission and the goals we set for our students. Teaching is more than just transferring knowledge—it’s about fostering environments conducive to growth, critical thinking, and lifelong learning. This e-book contains collective insights, experiences, and reflections from faculty participating in a Faculty Learning Community (FLC) a yearlong, structured, community …

Afit Strategic Plan: Accelerating Superiority 2023-2028, Afit Strategic Planning Committee, Air Force Institute Of Technology, Walter F. Jones

AFIT Documents

AFIT Vision: Leading defense-focused education, research, and consultation to accelerate military superiority across all domains.

AFIT Mission: Educate defense professionals to innovatively accomplish the deterrence and warfighting missions of the U.S. Air and Space Forces.

Graduate School Academic Catalog 2023-2024, Graduate School Of Engineering And Management, Air Force Institute Of Technology

AFIT Documents

The Graduate Catalog represents the offerings, programs, and requirements in effect at the time of publication.

To The Moon: Strategic Competition In The Cislunar Region, Shawn M. Willis

Faculty Publications

China’s advancing space capabilities, particularly in the cislunar region, call for increased cislunar space domain awareness on the part of the United States. US military and civilian decisionmakers must take into account the full scope of China’s cislunar plans and capabilities as the military builds space strategies and future force designs. The United States must also increase near-term investments that support more robust cislunar space domain awareness.

Atmospheric Meteorological Effects On Forecasting Daily Lightning Occurrence At Cape Canaveral Space Force Station, Jon Saul, Torrey J. Wagner, Eric G. Mbonimpa, Brent T. Langhals

Faculty Publications

As the Cape Canaveral Space Force Station and Kennedy Space Center increase their launch rate, any process that could assist in the automation of the currently-manual lightning forecast would be valuable. This work examines the possibility of machine-learning assistance with the daily lighting forecast which is produced by the 45th Weather Squadron. A dataset consisting of 34 lightning, pressure, temperature and windspeed measurements taken from 334 daily weather balloon (rawinsonde) launches in the timeframe 2012-2021 was examined. Models were created using recursive feature elimination on logistic regression and XGClassifier algorithms, as well as Bayesian and bandit optimization of neural network …

Machine Learning Prediction Of Dod Personal Property Shipment Costs, Tiffany Tucker, Torrey J. Wagner, Paul Auclair, Brent T. Langhals

Faculty Publications

U.S. Department of Defense (DoD) personal property moves account for 15% of all domestic and international moves - accurate prediction of their cost could draw attention to outlier shipments and improve budget planning. In this work 136,140 shipments between 13 personal property shipment hubs from April 2022 through March 2023 with a total cost of $1.6B were analyzed. Shipment cost was predicted using recursive feature elimination on linear regression and XGBoost algorithms, as well as through neural network hyperparameter sweeps. Modeling was repeated after removing 28 features related to shipment hub location and branch of service to examine their influence …

The Behavior Of Partially Coherent Twisted Space-Time Beams In Atmospheric Turbulence, Milo W. Hyde Iv

Faculty Publications

We study how atmospheric turbulence affects twisted space-time beams, which are non-stationary random optical fields whose space and time dimensions are coupled with a stochastic twist. Applying the extended Huygens–Fresnel principle, we derive the mutual coherence function of a twisted space-time beam after propagating a distance z through atmospheric turbulence of arbitrary strength. We specialize the result to derive the ensemble-averaged irradiance and discuss how turbulence affects the beam’s spatial size, pulse width, and space-time twist. Lastly, we generate, in simulation, twisted space-time beam field realizations and propagate them through atmospheric phase screens to validate our analysis.

Accelerating A Software Defined Satnav Receiver Using Multiple Parallel Processing Schemes, Logan Reich, Sanjeev Gunawardena, Michael Braasch

Faculty Publications

Excerpt: Satnav SDRs present many benefits in terms of flexibility and configurability. However, due to the high bandwidth signals involved in satnav SDR processing, the software must be highly optimized for the host platform in order to achieve acceptable runtimes. Modules such as sample decoding, carrier replica generation, carrier wipeoff, and correlation are computationally intensive components that benefit from accelerations.

Resilience Monitoring For Multi-Filter All-Source Navigation Framework With Assurance, Jonathon S. Gipson, Robert C. Leishman

Faculty Publications

The Autonomous and Resilient Management of All-source Sensors (ARMAS) framework monitors residual-space test statistics across unique sensor-exclusion banks of filters (known as subfilters) to provide a resilient, fault-resistant all-source navigation architecture with assurance. A critical assumption of this architecture, demonstrated in this paper, is fully overlapping state observability across all subfilters. All-source sensors, particularly those that only provide partial state information (altimeters, TDoA, AOB, etc.), do not intrinsically meet this requirement. This paper presents a novel method to monitor real-time overlapping position state observability and introduces an observability bank within the ARMAS framework, known as stable observability monitoring (SOM). SOM …

Fitting Solar Panel Brdf Parameters To Out-Of-Plane Empirical Data, Michael R. Gross

Theses and Dissertations

The bidirectional reflectance distribution function (BRDF) describes material reflectance by describing how incident irradiance reflects into all possible scatter angles as a function of incident angle. However, a solar panel has unique features that are not featured in any of these previously known models. A previous project at the Air Force Institute of Technology (AFIT) created a novel microfacet-like BRDF to model a solar panel with a prominent diffractive feature present which had not been previously modeled. This BRDF was coded into MATLAB for modeling purposes and C++ to test its speed with a MEX function call. A previous thesis …

A Statistical Analysis Of Sporadic-E Characteristics Associated With Gnss Radio Occultation Phase And Amplitude Scintillations, Daniel J. Emmons, Dong L. Wu, Nimalan Swarnalingam

Faculty Publications

Statistical GNSS-RO measurements of phase and amplitude scintillation are analyzed at the mid-latitudes in the local summer for a 100 km altitude. These conditions are known to contain frequent sporadic-E, and the S4-σ_ϕ trends provide insight into the statistical distributions of the sporadic-E parameters. Joint two-dimensional S4-σ_ϕ histograms are presented, showing roughly linear trends until the S4 saturates near 0.8. To interpret the measurements and understand the sporadic-E contributions, 10,000 simulations of RO signals perturbed by sporadic-E layers are performed using length, intensity, and vertical thickness distributions from previous studies, with the assumption that the sporadic-E layer acts …

Global Sporadic-E Occurrence Rate Climatology Using Gps Radio Occultation And Ionosonde Data, Travis J. Hodos, Omar A. Nava, Eugene V. Dao, Daniel J. Emmons

Faculty Publications

An updated global climatology of blanketing sporadic E (Es) is developed from a combined data set of Global Positioning System (GPS) radio occultation (RO) and ground-based ionosonde soundings over the period of September 2006–January 2019. A total of 46 sites and 3.2 million total soundings from the Global Ionosphere Radio Observatory network in combination with 3.0 million occultations from the Constellation Observing System for Meteorology, Ionosphere, and Climate constellation are used to calculate global occurrence rates (ORs) for two blanketing frequency thresholds: all blanketing sporadic-E with no limit on intensity (all-Es) and moderate-Es with fbEs …

Optimal Scheduling Of Aircraft Test And Evaluation Fleets To Balance Availability For Testing And Training, Sarah E. Hoops

Theses and Dissertations

The 96th Test Wing at Eglin Air Force Base manually schedules a fleet of approximately 26 aircraft to conduct a range of missions over a one-to-two year planning period. This study automates the scheduling process, does so in a manner that optimizes multiple planning goals related to aircraft availability for training, and provides the 96th Test Wing with a software tool for the implementation that can be used by operational analysts within the command. We formulate the scheduling problem as a multiobjective, nonlinear, binary integer math program that seeks to maximize both the lowest percent of time any aircraft is …

Cooperative Wide Area Search Algorithm Analysis Using Sub-Region Techniques, Shawn Whitney

Theses and Dissertations

Recent advances in small Unmmaned Aerial Vehicle (UAV) technology reinvigorates the need for additional research into Wide Area Search (WAS) algorithms for civilian and military applications. But due to the extremely large variability in UAV environments and design, Digital Engineering (DE) is utilized to reduce the time, cost, and energy required to advance this technology. DE also allows rapid design and evaluation of autonomous systems which utilize and support WAS algorithms. Modern WAS algorithms can be broadly classified into decision-based algorithms, statistical algorithms, and Artificial Intelligence (AI)/Machine Learning (ML) algorithms. This research continues on the work by Hatzinger and Gertsman …

Evaluating Deep Learning Explanations On Risc-V Assembly As A Reverse Engineering Aid, Daniel F. Koranek

Theses and Dissertations

This dissertation addresses several problems surrounding the detection of malware using deep learning models trained on assembly language examples. First, it examines the feasibility of detecting examples of malice using deep learning models trained on RISC-V instruction traces. Next, it examines whether models for detecting trace features and code features in RISC-V assembly can be made explainable (providing rationale for a model’s decision based upon the model’s internal workings) or interpretable (providing additional rationale as model output to support a human’s agreement with the model output). Third, this work examines ways in which it is possible to give additional contextual …

Active Attestation Of Embedded Systems, Mark M. Stephenson, Patrick A. Reber, Patrick J. Sweeney, Scott R. Graham

AFIT Patents

An active attestation apparatus verifies at runtime the integrity of untrusted machine code of an embedded system residing in a memory device while it is being run/used with while slowing the processing time less than other methods. The apparatus uses an integrated circuit chip containing a microcontroller and a reprogrammable logic device, such as a field programmable gate array (FPGA), to implement software attestation at runtime and in less time than is typically possible with comparable attestation approaches, while not requiring any halt of the processor in the microcontroller. The reprogrammable logic device includes functionality to load an encrypted version …

Transition-Metal Ions In Β-Ga2O3 Crystals: Identification Of Ni Acceptors, Timothy D. Gustafson, Nancy C. Giles, Brian C. Holloway, J. Jesenovec, B. L. Dutton, M. D. Mccluskey, Larry E. Halliburton

Faculty Publications

Excerpt: Transition-metal ions (Ni, Cu, and Zn) in β-Ga₂O₃ crystals form deep acceptor levels in the lower half of the bandgap. In the present study, we characterize the Ni acceptors in a Czochralski-grown crystal and find that their (0/−) level is approximately 1.40 eV above the maximum of the valence band.

Long-Distance Propagation Of 162 Mhz Shipping Information Links Associated With Sporadic E, Alex T. Chartier, Thomas R. Hanley, Daniel J. Emmons

Faculty Publications

This is a study of anomalous long-distance (>1000 km) radio propagation that was identified in United States Coast Guard monitors of automatic identification system (AIS) shipping transmissions at 162 MHz. Our results indicate this long-distance propagation is caused by dense sporadic E layers in the daytime ionosphere, which were observed by nearby ionosondes at the same time. This finding is surprising because it indicates these sporadic E layers may be far more dense than previously thought.

Generating Realistic Cyber Data For Training And Evaluating Machine Learning Classifiers For Network Intrusion Detection Systems, Marc W. Chalé, Nathaniel D. Bastian

Faculty Publications

No abstract provided.