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Evaluating Deep Learning Explanations On Risc-V Assembly As A Reverse Engineering Aid, Daniel F. Koranek
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 …
Fitting Solar Panel Brdf Parameters To Out-Of-Plane Empirical Data, Michael R. Gross
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 …
Quantum Error Detection Without Using Ancilla Qubits, Nicolas Guerrero
Quantum Error Detection Without Using Ancilla Qubits, Nicolas Guerrero
Theses and Dissertations
Quantum computers are beset by errors from a variety of sources. Although quantum error correction and detection codes have been developed since the 1990s, these codes require mid-circuit measurements in order to operate. In order to avoid these measurements we have developed a new error detection code that only requires state collapses at the end of the circuit, which we call no ancilla error detection (NAED). We investigate some of the mathematics behind NAED such as which codes can detect which errors. We then run NAED on three separate types of circuits: Greenberger–Horne–Zeilinger circuits, phase dependent circuits, and a quantum …
Orthogonal Arrays And Legendre Pairs, Kristopher N. Kilpatrick
Orthogonal Arrays And Legendre Pairs, Kristopher N. Kilpatrick
Theses and Dissertations
Well-designed experiments greatly improve test and evaluation. Efficient experiments reduce the cost and time of running tests while improving the quality of the information obtained. Orthogonal Arrays (OAs) and Hadamard matrices are used as designed experiments to glean as much information as possible about a process with limited resources. However, constructing OAs and Hadamard matrices in general is a very difficult problem. Finding Legendre pairs (LPs) results in the construction of Hadamard matrices. This research studies the classification problem of OAs and the existence problem of LPs. In doing so, it makes two contributions to the discipline. First, it improves …
Development Of A Security-Focused Multi-Channel Communication Protocol And Associated Quality Of Secure Service (Qoss) Metrics, Paul M. Simon
Development Of A Security-Focused Multi-Channel Communication Protocol And Associated Quality Of Secure Service (Qoss) Metrics, Paul M. Simon
Theses and Dissertations
The threat of eavesdropping, and the challenge of recognizing and correcting for corrupted or suppressed information in communication systems is a consistent challenge. Effectively managing protection mechanisms requires an ability to accurately gauge the likelihood or severity of a threat, and adapt the security features available in a system to mitigate the threat. This research focuses on the design and development of a security-focused communication protocol at the session-layer based on a re-prioritized communication architecture model and associated metrics. From a probabilistic model that considers data leakage and data corruption as surrogates for breaches of confidentiality and integrity, a set …
Analytic Case Study Using Unsupervised Event Detection In Multivariate Time Series Data, Jeremy M. Wightman
Analytic Case Study Using Unsupervised Event Detection In Multivariate Time Series Data, Jeremy M. Wightman
Theses and Dissertations
Analysis of cyber-physical systems (CPS) has emerged as a critical domain for providing US Air Force and Space Force leadership decision advantage in air, space, and cyberspace. Legacy methods have been outpaced by evolving battlespaces and global peer-level challengers. Automation provides one way to decrease the time that analysis currently takes. This thesis presents an event detection automation system (EDAS) which utilizes deep learning models, distance metrics, and static thresholding to detect events. The EDAS automation is evaluated with case study of CPS domain experts in two parts. Part 1 uses the current methods for CPS analysis with a qualitative …
Generative Methods, Meta-Learning, And Meta-Heuristics For Robust Cyber Defense, Marc W. Chale
Generative Methods, Meta-Learning, And Meta-Heuristics For Robust Cyber Defense, Marc W. Chale
Theses and Dissertations
Cyberspace is the digital communications network that supports the internet of battlefield things (IoBT), the model by which defense-centric sensors, computers, actuators and humans are digitally connected. A secure IoBT infrastructure facilitates real time implementation of the observe, orient, decide, act (OODA) loop across distributed subsystems. Successful hacking efforts by cyber criminals and strategic adversaries suggest that cyber systems such as the IoBT are not secure. Three lines of effort demonstrate a path towards a more robust IoBT. First, a baseline data set of enterprise cyber network traffic was collected and modelled with generative methods allowing the generation of realistic, …
Leveraging Subject Matter Expertise To Optimize Machine Learning Techniques For Air And Space Applications, Philip Y. Cho
Leveraging Subject Matter Expertise To Optimize Machine Learning Techniques For Air And Space Applications, Philip Y. Cho
Theses and Dissertations
We develop new machine learning and statistical methods that are tailored for Air and Space applications through the incorporation of subject matter expertise. In particular, we focus on three separate research thrusts that each represents a different type of subject matter knowledge, modeling approach, and application. In our first thrust, we incorporate knowledge of natural phenomena to design a neural network algorithm for localizing point defects in transmission electron microscopy (TEM) images of crystalline materials. In our second research thrust, we use Bayesian feature selection and regression to analyze the relationship between fighter pilot attributes and flight mishap rates. We …
Learning Robust Radio Frequency Fingerprints Using Deep Convolutional Neural Networks, Jose A. Gutierrez Del Arroyo
Learning Robust Radio Frequency Fingerprints Using Deep Convolutional Neural Networks, Jose A. Gutierrez Del Arroyo
Theses and Dissertations
Radio Frequency Fingerprinting (RFF) techniques, which attribute uniquely identifiable signal distortions to emitters via Machine Learning (ML) classifiers, are limited by fingerprint variability under different operational conditions. First, this work studied the effect of frequency channel for typical RFF techniques. Performance characterization using the multi-class Matthews Correlation Coefficient (MCC) revealed that using frequency channels other than those used to train the models leads to deterioration in MCC to under 0.05 (random guess), indicating that single-channel models are inadequate for realistic operation. Second, this work presented a novel way of studying fingerprint variability through Fingerprint Extraction through Distortion Reconstruction (FEDR), a …
Analysis Of Graph Layout Algorithms For Use In Command And Control Network Graphs, Matthew R. Stone
Analysis Of Graph Layout Algorithms For Use In Command And Control Network Graphs, Matthew R. Stone
Theses and Dissertations
This research is intended to determine which styles of layout algorithm are well suited to Command and Control (C2) network graphs to replace current manual layout methods. Manual methods are time intensive and an automated layout algorithm should decrease the time spent creating network graphs. Simulations on realistic synthetically generated graphs provide information to help infer which algorithms perform better than others on this problem. Data is generated using statistics drawn from multiple real world C2 network graphs. The three algorithms tested against this data are the Spectral algorithm, the Dot algorithm, and the Fruchterman-Reingold algorithm. The results include a …
Modern Approaches And Theoretical Extensions To The Multivariate Kolmogorov Smirnov Test, Gonzalo Hernando
Modern Approaches And Theoretical Extensions To The Multivariate Kolmogorov Smirnov Test, Gonzalo Hernando
Theses and Dissertations
Most statistical tests are fully developed for univariate data, but when inference is required for multivariate data, univariate tests risk information loss and interpretability. This research 1) derives and extends the multivariate Komolgorov Smirnov test for 2 and into m-dimensions, 2) derives small sample critical values for the KS test that are not reliant on sample size simulations or correlation between variables, 3) extends large sample estimations and current KS implementations, and 4) provides sample size and power calculations in order to enable experimental design with respect to testing for differences in distributions. Through extensive simulation, we demonstrate that our …
Improving Country Conflict And Peace Modeling: Datasets, Imputations, And Hierarchical Clustering, Benjamin D. Leiby
Improving Country Conflict And Peace Modeling: Datasets, Imputations, And Hierarchical Clustering, Benjamin D. Leiby
Theses and Dissertations
Many disparate datasets exist that provide country attributes covering political, economic, and social aspects. Unfortunately, this data often does not include all countries nor is the data complete for those countries included, as measured by the dataset’s missingness. This research addresses these dataset shortfalls in predicting country instability by considering country attributes in all aspects as well as in greater thresholds of missingness. First, a structured summary of past research is presented framed by a developed casual taxonomy and functional ontology. Additionally, a novel imputation technique for very large datasets is presented to account for moderate missingness in the expanded …
Efficiency Quantification For Pulsed-Source Digital Holographic Wavefront Sensing, Steven A. Owens
Efficiency Quantification For Pulsed-Source Digital Holographic Wavefront Sensing, Steven A. Owens
Theses and Dissertations
The efficiencies of a digital holography (DH) system in the pulsed configuration and the off-axis image plane recording geometry are analyzed. First, the system efficiencies of an infrared-wavelength DH system in a homodyne-pulsed configuration are measured and compared to those of a visible-wavelength DH system in a homodyne-continuous-wave (CW) configuration. The total-system, excess-reference-noise, shot-noise-limit, and mixing efficiencies of the pulsed-source system were found to be consistent with those of the CW-source system. This indicated no new efficiencies were necessary to characterize pulsed-source systems when no temporal delay exists between the pulses. The consistency of efficiencies also showed infrared DH systems …
Optimizing Optical Switching Of Non-Linear Optimizing Optical Switching Of Non-Linear Hyperbolic Metamaterials, James A. Ethridge
Optimizing Optical Switching Of Non-Linear Optimizing Optical Switching Of Non-Linear Hyperbolic Metamaterials, James A. Ethridge
Theses and Dissertations
Modern optical materials are engineered to be used as optical devices in specific applications, such as optical computing. For optical computing, efficient forms of a particular device, the optical switch, still have not been successfully demonstrated. This problem is addressed in this research through the use of designed optical metamaterials, specifically, hyperbolic metamaterials, which offer the possibility of large non-linear properties with a low switching intensity. One-dimensional layered hyperbolic metamaterials composed of alternating layers of metal and dielectric were used here, with ITO as the metal and SiO2 as the dielectric. The non-linear behavior of the ITO/SiO2 layered …
Statistical Inference On Desirability Function Optimal Points To Evaluate Multi-Objective Response Surfaces, Peter A. Calhoun
Statistical Inference On Desirability Function Optimal Points To Evaluate Multi-Objective Response Surfaces, Peter A. Calhoun
Theses and Dissertations
A shortfall of the Derringer and Suich (1980) desirability function is lack of inferential methods to quantify uncertainty. Most articles for addressing uncertainty usually involve robust methods, providing a point estimate that is less affected by variation. Few articles address confidence intervals or bands but not specifically for the Derringer and Suich method. This research provides two valuable contributions to the field of response surface methodology. The first contribution is evaluating the effect of correlation and plane angles on Derringer and Suich optimal solutions. The second contribution proposes and compares 8 inferential methods--both univariate and multivariate--for creating confidence intervals on …
Analyzing Microarchitectural Residue In Various Privilege Strata To Identify Computing Tasks, Tor J. Langehaug
Analyzing Microarchitectural Residue In Various Privilege Strata To Identify Computing Tasks, Tor J. Langehaug
Theses and Dissertations
Modern multi-tasking computer systems run numerous applications simultaneously. These applications must share hardware resources including the Central Processing Unit (CPU) and memory while maximizing each application’s performance. Tasks executing in this shared environment leave residue which should not reveal information. This dissertation applies machine learning and statistical analysis to evaluate task residue as footprints which can be correlated to identify tasks. The concept of privilege strata, drawn from an analogy with physical geology, organizes the investigation into the User, Operating System, and Hardware privilege strata. In the User Stratum, an adversary perspective is taken to build an interrogator program that …
Enabling Rapid Chemical Analysis Of Plutonium Alloys Via Machine Learning-Enhanced Atomic Spectroscopy Techniques, Ashwin P. Rao
Enabling Rapid Chemical Analysis Of Plutonium Alloys Via Machine Learning-Enhanced Atomic Spectroscopy Techniques, Ashwin P. Rao
Theses and Dissertations
Analytical atomic spectroscopy methods have the potential to provide solutions for rapid, high fidelity chemical analysis of plutonium alloys. Implementing these methods with advanced analytical techniques can help reduce the chemical analysis time needed for plutonium pit production, directly enabling the 80 pit-per-year by 2030 manufacturing goal outlined in the 2018 Nuclear Posture Review. Two commercial, handheld elemental analyzers were validated for potential in situ analysis of Pu. A handheld XRF device was able to detect gallium in a Pu surrogate matrix with a detection limit of 0.002 wt% and a mean error of 8%. A handheld LIBS device was …
Scheduling For Space Tracking And Heterogeneous Sensor Environments, Gabriel H. Greve
Scheduling For Space Tracking And Heterogeneous Sensor Environments, Gabriel H. Greve
Theses and Dissertations
This dissertation draws on the fields of heuristic and meta-heuristic algorithm development, resource allocation problems, and scheduling to address key Air Force problems. The world runs on many schedules. People depend upon them and expect these schedules to be accurate. A process is needed where schedules can be dynamically adjusted to allow tasks to be completed efficiently. For example, the Space Surveillance Network relies on a schedule to track objects in space. The schedule must use sensor resources to track as many high-priority satellites as possible to obtain orbit paths and to warn of collision paths. Any collisions that occurred …
Methods For Focal Plane Array Resolution Estimation Using Random Laser Speckle In Non-Paraxial Geometries, Phillip J. Plummer
Methods For Focal Plane Array Resolution Estimation Using Random Laser Speckle In Non-Paraxial Geometries, Phillip J. Plummer
Theses and Dissertations
The infrared (IR) imaging community has a need for direct IR detector evaluation due to the continued demand for small pixel pitch detectors, the emergence of strained-layer-super-lattice devices, and the associated lateral carrier diffusion issues. Conventional laser speckle-based modulation transfer function (MTF) estimation is dependent on Fresnel propagation and a wide-sense-stationary input random process, limiting the use of this approach for lambda (wavelength)-scale IR devices. This dissertation develops two alternative methodologies for speckle-based resolution evaluation of IR focal plane arrays (FPAs). Both techniques are formulated using Rayleigh-Sommerfield electric field propagation, making them valid in the non-paraxial geometries dictated for resolution …
Full Pattern Analysis And Comparison Of The Center Fed And Offset Fed Cassegrain Antennas With Large Focal Length To Diameter Ratios For High Power Microwave Transmission, Derek W. Mantzke
Theses and Dissertations
High power microwaves (HPM) have been a topic of research since the Cold War era. This paper will present a comparison between two Cassegrain-type antennas: the axially, or center fed, and the offset fed. Specifically, the 10 GHz operating frequency will be investigated with large focal length to diameter () ratios. Beam patterns which encompass the entire radiation pattern will be included for data validation and optimization. The simulations will follow a design of experiments factorial model to ensure all possible combinations of prescribed parameters are included, including an analysis of variance (ANOVA) study to find parameter influence on the …
Innovative Heuristics To Improve The Latent Dirichlet Allocation Methodology For Textual Analysis And A New Modernized Topic Modeling Approach, Jamie T. Zimmerman
Innovative Heuristics To Improve The Latent Dirichlet Allocation Methodology For Textual Analysis And A New Modernized Topic Modeling Approach, Jamie T. Zimmerman
Theses and Dissertations
Natural Language Processing is a complex method of data mining the vast trove of documents created and made available every day. Topic modeling seeks to identify the topics within textual corpora with limited human input into the process to speed analysis. Current topic modeling techniques used in Natural Language Processing have limitations in the pre-processing steps. This dissertation studies topic modeling techniques, those limitations in the pre-processing, and introduces new algorithms to gain improvements from existing topic modeling techniques while being competitive with computational complexity. This research introduces four contributions to the field of Natural Language Processing and topic modeling. …
Evaluating A Statistical-Based Assessment Tool For Stratifying Risk Among U.S. Air Force Organizations, Tiffany A. Low
Evaluating A Statistical-Based Assessment Tool For Stratifying Risk Among U.S. Air Force Organizations, Tiffany A. Low
Theses and Dissertations
The Air Force Inspection System is a proponent of utilizing a risk-based sampling strategy (RBSS) for conducting inspections from major command levels down to the unit level. The strategy identifies areas deemed most important or risky by commanders and prioritizes them accordingly for an independent assessment by the Inspector General. While Air Force regulation specifies the need to use a RBSS for inspection, the implementation process is delegated to individual commands and, subsequently, wings. The 23rd Wing, the sponsor for this research, directed us to analyze a RBSS tool highlighted as an example from which to adopt for those units …
Formal Spark Verification Of Various Resampling Methods In Particle Filters, Osiris J. Terry
Formal Spark Verification Of Various Resampling Methods In Particle Filters, Osiris J. Terry
Theses and Dissertations
The software verification in this thesis concentrates on verifying a particle filter for use in tracking and estimation, a key application area for the Air Force. The development and verification process described in this thesis is a demonstration of the power, limitation, and compromises involved in applying automated software verification tools to critical embedded software applications.
Improving Anonymized Search Relevance With Natural Language Processing And Machine Learning, Niko A. Petrocelli
Improving Anonymized Search Relevance With Natural Language Processing And Machine Learning, Niko A. Petrocelli
Theses and Dissertations
Users often sacrifice personal data for more relevant search results, presenting a problem to communities that desire both search anonymity and relevant results. To balance these priorities, this research examines the impact of using Siamese networks to extend word embeddings into document embeddings and detect similarities between documents. The predicted similarity can locally re-rank search results provided from various sources. This technique is leveraged to limit the amount of information collected from a user by a search engine. A prototype is produced by applying the methodology in a real-world search environment. The prototype yielded an additional function of finding new …
Evaluating Semantic Matching Techniques For Technical Documents, Rain F. Dartt
Evaluating Semantic Matching Techniques For Technical Documents, Rain F. Dartt
Theses and Dissertations
Machine learning models that employ NLP techniques have become more widely accessible, making them an attractive solution for text and document classification tasks traditionally accomplished by humans. Two such use cases are matching the specialized experience required for a job to statements in applicant resumes, and finding and labelling clauses in legal contracts The AFMC has an immediate need for solutions to civilian hiring. However, there is currently no truth data to validate against. A similar task is contract understanding for which there is the CUAD, a recently published repository of 510 contracts manually labelled by legal experts. The presented …
Telemetry Data Mining For Unmanned Aircraft Systems, Li Yu
Telemetry Data Mining For Unmanned Aircraft Systems, Li Yu
Theses and Dissertations
With ever more data becoming available to the US Air Force, it is vital to develop effective methods to leverage this strategic asset. Machine learning (ML) techniques present a means of meeting this challenge, as these tools have demonstrated successful use in commercial applications. For this research, three ML methods were applied to a unmanned aircraft system (UAS) telemetry dataset with the aim of extracting useful insight related to phases of flight. It was shown that ML provides an advantage in exploratory data analysis and as well as classification of phases. Neural network models demonstrated the best performance with over …
Exploiting The Iot Through Network-Based Covert Channels, Kyle S. Harris
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 …
Dds-Cerberus: Improving Security In Dds Middleware Using Kerberos Tickets, Andrew T. Park
Dds-Cerberus: Improving Security In Dds Middleware Using Kerberos Tickets, Andrew T. Park
Theses and Dissertations
The military deploys many IoT in battlefield operations to provide information on terrain and enemy combatants. It also deploys automated robots or UAVs where securing and trusting collected data is essential. Choosing the middleware that handles this message transfer is crucial for real-time operations. Networks with multiple entities, including IoT devices, UAVs, and small computers, require robust middleware facilitating message sending in real-time. Ideally, the middleware would provide QoS to handle lost packets and retransmissions in lossy environments, especially between low-power machines. DDS is a middleware that implements real-time and QoS capabilities by sending messages, not based on endpoints but …
Carbon Estimation And Decision Making In Usaf Acquisition, Robert F. Gray
Carbon Estimation And Decision Making In Usaf Acquisition, Robert F. Gray
Theses and Dissertations
Recent executive orders and international agreements require the United States to significantly reduce its carbon and greenhouse gas emissions. The DoD is a significant contributor to the carbon emissions of the USA and will be required to reduce the emissions. Therefore, in order to make appropriate programmatic decisions the DoD needs to develop an appropriate method for estimating carbon and making programmatic decisions; trading-off carbon emissions with the traditional cost-schedule-performance metrics. This thesis examines the possibility of developing a model that can be used to estimate the carbon footprint of producing a system before detailed engineering designed have been complete.
Applying Models Of Circadian Stimulus To Explore Ideal Lighting Configurations, Alexander J. Price
Applying Models Of Circadian Stimulus To Explore Ideal Lighting Configurations, Alexander J. Price
Theses and Dissertations
Increased levels of time are spent indoors, decreasing human interaction with nature and degrading photoentrainment, the synchronization of circadian rhythms with daylight variation. Military imagery analysts, among other professionals, are required to work in low light level environments to limit power consumption or increase contrast on display screens to improve detail detection. Insufficient exposure to light in these environments results in inadequate photoentrainment which is associated with degraded alertness and negative health effects. Recent research has shown that both the illuminance (i.e., perceived intensity) and wavelength of light affect photoentrainment. Simultaneously, modern lighting technologies have improved our ability to construct …