Computer Engineering Commons^™

Virtual Battlespace Behavior Generation Through Class Imitation, Bryon K. Fryer Jr.

Theses and Dissertations

Military organizations need realistic training scenarios to ensure mission readiness. Developing the skills required to differentiate combatants from non-combatants is very important for ensuring the international law of armed conflict is upheld. In Simulated Training Environments, one of the open challenges is to correctly simulate the appearance and behavior of combatant and non-combatant agents in a realistic manner. This thesis outlines the construction of a data driven agent that is capable of imitating the behaviors of the Virtual BattleSpace 2 behavior classes while our agent is configured to advance to a geographically specific goal. The approach and the resulting agent …

A Multi Agent System For Flow-Based Intrusion Detection Using Reputation And Evolutionary Computation, David Hancock

Theses and Dissertations

The rising sophistication of cyber threats as well as the improvement of physical computer network properties present increasing challenges to contemporary Intrusion Detection (ID) techniques. To respond to these challenges, a multi agent system (MAS) coupled with flow-based ID techniques may effectively complement traditional ID systems. This paper develops: 1) a scalable software architecture for a new, self-organized, multi agent, flow-based ID system; and 2) a network simulation environment suitable for evaluating implementations of this MAS architecture and for other research purposes. Self-organization is achieved via 1) a reputation system that influences agent mobility in the search for effective vantage …

Malicious And Malfunctioning Node Detection Via Observed Physical Layer Data, Tyler J. Hardy

Theses and Dissertations

There are many mechanisms that can cause inadequate or unreliable information in sensor networks. A user of the network might be interested in detecting and classifying specific sensors nodes causing these problems. Several network layer based trust methods have been developed in previous research to assess these issues; in contrast this work develops a trust protocol based on observations of physical layer data collected by the sensors. Observations of physical layer data are used for decisions and calculations, and are based on just the measurements collected by the sensors. Although this information is packaged and distributed on the network layer, …

Adaptive Quality Of Service Engine With Dynamic Queue Control, James D. Haught

Theses and Dissertations

While the current routing and congestion control algorithms in use today are often sufficient for networks with relatively static topology, these algorithms may not be sufficient for military networks where a certain level of quality of service (QoS) needs to be achieved to complete a mission. Current networking technology limits a network's ability to adapt to changes and interactions in the network, often resulting in sub-optimal performance. This research investigates the use of queue size predictions to create a network controller to optimize computer networks. These queue size predictions are made possible through the use of Kalman filters to detect …

Holistic Network Defense: Fusing Host And Network Features For Attack Classification, Jenny W. Ji

Theses and Dissertations

This work presents a hybrid network-host monitoring strategy, which fuses data from both the network and the host to recognize malware infections. This work focuses on three categories: Normal, Scanning, and Infected. The network-host sensor fusion is accomplished by extracting 248 features from network traffic using the Fullstats Network Feature generator and from the host using text mining, looking at the frequency of the 500 most common strings and analyzing them as word vectors. Improvements to detection performance are made by synergistically fusing network features obtained from IP packet flows and host features, obtained from text mining port, processor, logon …

Covert Channels Within Irc, Wayne C. Henry

Theses and Dissertations

The exploration of advanced information hiding techniques is important to understand and defend against illicit data extractions over networks. Many techniques have been developed to covertly transmit data over networks, each differing in their capabilities, methods, and levels of complexity. This research introduces a new class of information hiding techniques for use over Internet Relay Chat (IRC), called the Variable Advanced Network IRC Stealth Handler (VANISH) system. Three methods for concealing information are developed under this framework to suit the needs of an attacker. These methods are referred to as the Throughput, Stealth, and Baseline scenarios. Each is designed for …

Polarimetric Enhancements To Electro-Optical Aided Navigation Techniques, Jeremiah D. Johnson

Theses and Dissertations

Navigation in indoor and urban environments by small unmanned systems is a topic of interest for the Air Force. The Advanced Navigation Technology Center at the Air Force Institute of Technology is continually looking for novel approaches to navigation in GPS deprived environments. Inertial sensors have been coupled with image aided concepts, such as feature tracking, with good results. However, feature density in areas with large, flat, smooth surfaces tends to be low. Polarimetric sensors have been used for surface reconstruction, surface characterization and outdoor navigation. This thesis combines aspects of some of these algorithms along with a realistic, micro-facet …

Routing Uavs To Co-Optimize Mission Effectiveness And Network Performance With Dynamic Programming, Spenser D. Lee

Theses and Dissertations

In support of the Air Force Research Laboratory's (AFRL) vision of the layered sensing operations center, command and control intelligence surveillance and reconnaissance (C2ISR) more focus must be placed on architectures that support information systems, rather than just the information systems themselves. By extending the role of UAVs beyond simply intelligence, surveillance, and reconnaissance (ISR) operations and into a dual-role with networking operations we can better utilize our information assets. To achieve the goal of dual-role UAVs, a concrete approach to planning must be taken. This research defines a mathematical model and a non-trivial deterministic algorithmic approach to determining UAV …

An Architecture For Improving Timeliness And Relevance Of Cyber Incident Notifications, James L. Miller

Theses and Dissertations

This research proposes a communications architecture to deliver timely and relevant cyber incident notifications to dependent mission stakeholders. This architecture, modeled in Unified Modeling Language (UML), eschews the traditional method of pushing notifications via message as dictated in Air Force Instruction 33-138. It instead shifts to a pull or publish and subscribe method of making notifications. Shifting this paradigm improves the notification process by empowering mission owners to identify those resources on which they depend for mission accomplishment, provides a direct conduit between providing and dependent mission owners for notifications when an incident occurs, and provides a shared representation for …

Evaluating Information Assurance Control Effectiveness On An Air Force Supervisory Control And Data Acquisition (Scada) System, Jason R. Nielsen

Theses and Dissertations

Supervisory Control and Data Acquisition (SCADA) systems are increasingly being connected to corporate networks which has dramatically expanded their attack surface to remote cyber attack. Adversaries are targeting these systems with increasing frequency and sophistication. This thesis seeks to answer the research question addressing which Information Assurance (IA) controls are most significant for network defenders and SCADA system managers/operators to focus on in order to increase the security of critical infrastructure systems against a Stuxnet-like cyber attack. This research applies the National Institute of Science and Technology (NIST) IA controls to an attack tree modeled on a remote Stuxnet-like cyber …

Defensive Cyber Battle Damage Assessment Through Attack Methodology Modeling, Ryan T. Ostler

Theses and Dissertations

Due to the growing sophisticated capabilities of advanced persistent cyber threats, it is necessary to understand and accurately assess cyber attack damage to digital assets. This thesis proposes a Defensive Cyber Battle Damage Assessment (DCBDA) process which utilizes the comprehensive understanding of all possible cyber attack methodologies captured in a Cyber Attack Methodology Exhaustive List (CAMEL). This research proposes CAMEL to provide detailed knowledge of cyber attack actions, methods, capabilities, forensic evidence and evidence collection methods. This product is modeled as an attack tree called the Cyber Attack Methodology Attack Tree (CAMAT). The proposed DCBDA process uses CAMAT to analyze …

Automated Analysis Of Arm Binaries Using The Low-Level Virtual Machine Compiler Framework, Jeffrey B. Scott

Theses and Dissertations

Binary program analysis is a critical capability for offensive and defensive operations in Cyberspace. However, many current techniques are ineffective or time-consuming and few tools can analyze code compiled for embedded processors such as those used in network interface cards, control systems and mobile phones. This research designs and implements a binary analysis system, called the Architecture-independent Binary Abstracting Code Analysis System (ABACAS), which reverses the normal program compilation process, lifting binary machine code to the Low-Level Virtual Machine (LLVM) compiler's intermediate representation, thereby enabling existing security-related analyses to be applied to binary programs. The prototype targets ARM binaries but …

Kernelized Locality-Sensitive Hashing For Fast Image Landmark Association, Mark A. Weems

Theses and Dissertations

As the concept of war has evolved, navigation in urban environments where GPS may be degraded is increasingly becoming more important. Two existing solutions are vision-aided navigation and vision-based Simultaneous Localization and Mapping (SLAM). The problem, however, is that vision-based navigation techniques can require excessive amounts of memory and increased computational complexity resulting in a decrease in speed. This research focuses on techniques to improve such issues by speeding up and optimizing the data association process in vision-based SLAM. Specifically, this work studies the current methods that algorithms use to associate a current robot pose to that of one previously …

Spear Phishing Attack Detection, David T. Merritt

Theses and Dissertations

This thesis addresses the problem of identifying email spear phishing attacks, which are indicative of cyber espionage. Spear phishing consists of targeted emails sent to entice a victim to open a malicious file attachment or click on a malicious link that leads to a compromise of their computer. Current detection methods fail to detect emails of this kind consistently. The SPEar phishing Attack Detection system (SPEAD) is developed to analyze all incoming emails on a network for the presence of spear phishing attacks. SPEAD analyzes the following file types: Windows Portable Executable and Common Object File Format (PE/COFF), Adobe Reader, …

Simultaneous Range/Velocity Detection With An Ultra-Wideband Random Noise Radar Through Fully Digital Cross-Correlation In The Time Domain, James R. Lievsay

Theses and Dissertations

This research effort examines the theory, application, and results of applying two-dimensional cross-correlation in the time domain to ultra-wideband (UWB) random noise waveforms for simultaneous range and velocity estimation. When applying common Doppler processing techniques to random noise waveforms for the purpose of velocity estimation, the velocity resolution degrades as the signal bandwidth or the target speed increase. To mitigate the degradation, the Doppler approximation is not utilized, and instead, wideband signal processing theory is applied in the time domain. The results show that by accurately interpolating each sample in the digitized reference signal, a target's velocity and range can …

Creating A Network Model For The Integration Of Dynamic And Static Supervisory Control And Data Acquisition (Scada) Test Environment, Marlon Coerbell

Theses and Dissertations

Since 9/11 protecting our critical infrastructure has become a national priority. Presidential Decision Directive 63 mandates and lays a foundation for ensuring all aspects of our nation's critical infrastructure remain secure. Key in this debate is the fact that much of our electrical power grid fails to meet the spirit of this requirement. My research leverages the power afforded by Electric Power and Communication Synchronizing Simulator (EPOCHS) developed with the assistance of Dr. Hopkinson, et al. The power environment is modeled in an electrical simulation environment called PowerWorld©. The network is modeled in OPNET® and populated with self-similar network and …

Trust Management And Security In Satellite Telecommand Processing, Mark C. Duncan

Theses and Dissertations

New standards and initiatives in satellite system architecture are moving the space industry to more open and efficient mission operations. Primarily, these standards allow multiple missions to share standard ground and space based resources to reduce mission development and sustainment costs. With the benefits of these new concepts comes added risk associated with threats to the security of our critical space assets in a contested space and cyberspace domain. As one method to mitigate threats to space missions, this research develops, implements, and tests the Consolidated Trust Management System (CTMS) for satellite flight software. The CTMS architecture was developed using …

Exploring Trade-Offs In Auv Controller Design For Shark Tracking, Louis James Bertsch Iv

Master's Theses

This thesis explores the use of an Autonomous Underwater Vehicle (AUV) to track and pursue a tagged shark through the water. A controller was designed to take bearing and range to the shark tag and then control the AUV to pursue it.

First, the ability of a particle filter to provide an accurate estimation of the location of the shark relative to the AUV is explored. Second, the ability of the AUV to follow the shark's path through the water is shown. This ability allows for localized environmental sampling of the shark's preferred path. Third, various path weightings are used …

Single-Beam Holographic Tomography Creates Images In Three Dimensions, George Nehmetallah, Partha P. Banerjee, Nickolai Kukhtarev

Electrical and Computer Engineering Faculty Publications

In digital holography (DH), the interference between light scattered from an object and a reference wave is recorded using a CCD camera. DH has various advantages over analog holography: no film processing is needed, reconstruction is performed using numerical methods, and no further experimental setup is necessary. However, one of the disadvantages of DH is that current CCDs have a resolution of approximately 1,000 lines/mm, which is less than that of photographic film.

Anisotropic Electrical Properties Of Nanostructured Metallic Thin Films, Mo Ahoujja, Piyush Shah, Andrew Saragan, Said Elhamri, Elena A. Guliants

Electrical and Computer Engineering Faculty Publications

High surface area, porous, metallic (Ti, Cr) nanorod thin ¯lms with columnar microstructure can be deposited using conventional physical vapor deposition technique of E-beam evaporation. The technique relies on the physical vapor deposition onto a static substrate oriented in a position where °ux from the source material (Ti, Cr) arrives at oblique angle. The adatoms provides geometrical shadowing which results in growth of nanorod columns in the direction of vapor source. Deposition conditions such as angle of the incoming vapor °ux, substrate temperature, surface di®usion etc. have strong in°uence on the shape and arrangement of the columnar thin ¯lms. In …

Optimizing Trajectories For Unmanned Aerial Vehicles (Uavs) Patrolling The Border, Chris Kiekintveld, Vladik Kreinovich, Octavio Lerma

Departmental Technical Reports (CS)

Estimating Covariance For Privacy Case Under Interval (And Fuzzy) Uncertainty, Ali Jalal-Kamali, Vladik Kreinovich, Luc Longpre

Departmental Technical Reports (CS)

Knowledge Annotations In Scientific Workflows: An Implementation In Kepler, Aida Gandara, George Chin Jr., Paulo Pinheiro Da Silva, Signe White, Chandrika Sivaramakrishnan, Terence Critchlow

Departmental Technical Reports (CS)

Scientific research products are the result of long-term collaborations between teams. Scientific workflows are capable of helping scientists in many ways including collecting information about how research was conducted (e.g., scientific workflow tools often collect and manage information about datasets used and data transformations). However, knowledge about why data was collected is rarely documented in scientific workflows. In this paper we describe a prototype system built to support the collection of scientific expertise that influences scientific analysis. Through evaluating a scientific research effort underway at the Pacific Northwest National Laboratory, we identified features that would most benefit PNNL scientists in …

Quantifying Performance In Fading Channels Using The Sampling Property Of A Delta Function, Won Mee Jang

Department of Electrical and Computer Engineering: Faculty Publications (to 2015)

We apply the sampling property of a delta function to obtain the probability of error in fading channels. Our approach reduces the integration to a sampling. The sampling point is obtained in terms of fading parameters and the average signal-to-noise ratio (SNR) to provide the closed form solution of the performance.

Modified Fourier-Motzkin Elimination Algorithm For Reducing Systems Of Linear Inequalities With Unconstrained Parameters, Mario Bencomo, Luis Gutierrez, Martine Ceberio

Departmental Technical Reports (CS)

The need for eliminating redundancies in systems of linear inequalities arises in many applications. In linear programming (LP), one seeks a solution that optimizes a given linear objective function subject to a set of linear constraints, sometimes posed as linear inequalities. Linear inequalities also arise in the context of tensor decomposition. Due to the lack of uniqueness in higher-order tensor decomposition, non-negativity constraints are imposed on the decomposition factors, yielding systems of linear inequalities. Eliminating redundancies in such systems can reduce the number of computations, and hence improve computation times in applications.

Towards Faster Estimation Of Statistics And Odes Under Interval, P-Box, And Fuzzy Uncertainty: From Interval Computations To Rough Set-Related Computations, Vladik Kreinovich

Departmental Technical Reports (CS)

Interval computations estimate the uncertainty of the result of data processing in situations in which we only know the upper bounds $\Delta$ on the measurement errors. In interval computations, at each intermediate stage of the computation, we have intervals of possible values of the corresponding quantities. As a result, we often have bounds with excess width. One way to remedy this problem is to extend interval technique to rough-set computations, where on each stage, in addition to intervals of possible values of the quantities, we also keep rough sets representing possible values of pairs (triples, etc.).

How To Combine Probabilistic And Possibilistic (Expert) Knowledge: Uniqueness Of Reconstruction In Yager's (Product) Approach, Nitaya Buntao, Vladik Kreinovich

Departmental Technical Reports (CS)

Often, about the same real-life system, we have both measurement-related probabilistic information expressed by a probability measure P(S) and expert-related possibilistic information expressed by a possibility measure M(S). To get the most adequate idea about the system, we must combine these two pieces of information. For this combination, R. Yager -- borrowing an idea from fuzzy logic -- proposed to use the simple product t-norm, i.e., to consider a set function f(S) = P(S) * M(S). A natural question is: can we uniquely reconstruct the two parts of knowledge from this function f(S)? In this paper, we prove that while …

Estimating Risk Of Extreme And Catastrophic Events Under Interval Uncertainty, Nitaya Buntao, Vladik Kreinovich

Departmental Technical Reports (CS)

In many application areas, we encounter heavy-taildistributions -- for example, such distributions are ubiquitousin financial applications. These distributions are oftendescribed by Pareto law. There exist techniques for estimatingthe parameters of such the corresponding Pareto distributionsbased on the sample x₁, ..., x_n. In practice, we oftenonly know the values x_i with interval uncertainty. In thispaper, we show how to estimate the parameters of the Paretodistribution under such uncertainty and how to describe deviationand dependence for general heavy-tailed distributions.

Scalable Correct Memory Ordering Via Relativistic Programming, Josh Triplett, Philip William Howard, Paul E. Mckenney, Jonathan Walpole

Computer Science Faculty Publications and Presentations

We propose and document a new concurrent programming model, relativistic programming. This model allows readers to run concurrently with writers, without blocking or using expensive synchronization. Relativistic programming builds on existing synchronization primitives that allow writers to wait for current readers to finish with minimal reader overhead. Our methodology models data structures as graphs, and reader algorithms as traversals of these graphs; from this foundation we show how writers can implement arbitrarily strong ordering guarantees for the visibility of their writes, up to and including total ordering.

Generalized Construction Of Scalable Concurrent Data Structures Via Relativistic Programming, Josh Triplett, Paul E. Mckenney, Philip W. Howard, Jonathan Walpole

Computer Science Faculty Publications and Presentations

We present relativistic programming, a concurrent programming model based on shared addressing, which supports efficient, scalable operation on either uniform shared-memory or distributed shared- memory systems. Relativistic programming provides a strong causal ordering property, allowing a series of read operations to appear as an atomic transaction that occurs entirely between two ordered write operations. This preserves the simple immutable-memory programming model available via mutual exclusion or transactional memory. Furthermore, relativistic programming provides joint-access parallelism, allowing readers to run concurrently with a writer on the same data. We demonstrate a generalized construction technique for concurrent data structures based on relativistic programming, …