Computer Engineering Commons^™

Distributed Wireless Algorithms For Rfid Systems: Grouping Proofs And Cardinality Estimation, Vanya D. Cherneva

LSU Doctoral Dissertations

The breadth and depth of the use of Radio Frequency Identification (RFID) are becoming more substantial. RFID is a technology useful for identifying unique items through radio waves. We design algorithms on RFID-based systems for the Grouping Proof and Cardinality Estimation problems.

A grouping-proof protocol is evidence that a reader simultaneously scanned the RFID tags in a group. In many practical scenarios, grouping-proofs greatly expand the potential of RFID-based systems such as supply chain applications, simultaneous scanning of multiple forms of IDs in banks or airports, and government paperwork. The design of RFID grouping-proofs that provide optimal security, privacy, and …

Robotic Motion Generation By Using Spatial-Temporal Patterns From Human Demonstrations, Yongqiang Huang

USF Tampa Graduate Theses and Dissertations

Robots excel in manufacturing facilities because the tasks are repetitive and do not change. However, when the tasks change, which happens in almost all tasks that humans perform daily, such as cutting, pouring, and grasping, etc., robots perform much worse. We aim at teaching robots to perform tasks that are subject to change using demonstrations collected from humans, a problem referred to as learning from demonstration (LfD).

LfD consists of two parts: the data of human demonstrations, and the algorithm that extracts knowledge from the data to perform the same motions. Similarly, this thesis is divided into two parts. The …

Force Feedback And Intelligent Workspace Selection For Legged Locomotion Over Uneven Terrain, John Rippetoe

USF Tampa Graduate Theses and Dissertations

Legged robots present an incredible opportunity for humanity to conduct dangerous operations such as search and rescue, disaster recovery, and planetary exploration without ever placing themselves in harms way. The ability of a leg to more freely dictate its shape, orientation, and length gives it tremendous mobility and adaptability demanded of a system intended for operation outside of a controlled environment. However, one only need look at the average cat, dog, or friendly neighborhood squirrel to understand the immense gap that exists between what is possible of legged systems and their current set of capabilities.

Areas of study relevant to …

Immersive Virtual Reality Attacks And The Human Joystick, Peter Casey, Ibrahim Baggili, Ananya Yarramreddy

Electrical & Computer Engineering and Computer Science Faculty Publications

This is one of the first accounts for the security analysis of consumer immersive Virtual Reality (VR) systems. This work breaks new ground, coins new terms, and constructs proof of concept implementations of attacks related to immersive VR. Our work used the two most widely adopted immersive VR systems, the HTC Vive, and the Oculus Rift. More specifically, we were able to create attacks that can potentially disorient users, turn their Head Mounted Display (HMD) camera on without their knowledge, overlay images in their field of vision, and modify VR environmental factors that force them into hitting physical objects and …

A Comparison Of X86 Computer Architecture Simulators, Ayaz Akram, Lina Sawalha

Faculty Research and Creative Activities Award (FRACAA)

Computer architecture simulators are widely used to evaluate different design options and tradeoffs. This work explores different x86 computer architecture simulators and shows the experimental error of the simulators compared to real hardware runs. We selected gem5, Sniper, MARSSx86 and Zsim, and configured them to model one of the state-of-the- art high-performance processors, Intel’s Haswell microarchitecture. We compared simulators features and statistics, and quantified the experimental error of simulators for single- and multi-core runs compared to a real hardware platform. Finally, we pointed some causes of inaccuracies resulted by the simulators.

Near Real-Time Rf-Dna Fingerprinting For Zigbee Devices Using Software Defined Radios, Frankie A. Cruz

Theses and Dissertations

Low-Rate Wireless Personal Area Network(s) (LR-WPAN) usage has increased as more consumers embrace Internet of Things (IoT) devices. ZigBee Physical Layer (PHY) is based on the Institute of Electrical and Electronics Engineers (IEEE) 802.15.4 specification designed to provide a low-cost, low-power, and low-complexity solution for Wireless Sensor Network(s) (WSN). The standard’s extended battery life and reliability makes ZigBee WSN a popular choice for home automation, transportation, traffic management, Industrial Control Systems (ICS), and cyber-physical systems. As robust and versatile as the standard is, ZigBee remains vulnerable to a myriad of common network attacks. Previous research involving Radio Frequency-Distinct Native Attribute …

Autonomous Association Of Geo Rso Observations Using Deep Neural Networks, Ian W. Mcquaid

Theses and Dissertations

Ground-based non-resolved optical observations of resident space objects (RSOs) in geosynchronous orbit (GEO) represent the majority of the space surveillance network’s (SSN’s) deep-space tracking. Reliable and accurate tracking necessitates temporal separation of the observations. This requires that subsequent observations be associated with prior observations of a given RSO before they can be used to create or refine that RSO’s ephemeris. The use of astrometric data (e.g. topocentric angular position) alone for this association task is complicated by RSO maneuvers between observations, and by RSOs operating in close proximity. Accurately associating an observation with an RSO thus motivates the use of …

A Quantitative Analysis Of The Fusion Of 3-D Scanning Lidar Systems And 2-D Imaging Systems, Michael F. Milton Jr.

Theses and Dissertations

This research will demonstrate the feasibility of fusing the superior spatial resolution of a 2-D imaging system with the precise range to target information of a 3-D imaging system to create a LIDAR imaging system that can accurately find what and where a target is. The 3-D imaging system will use a scanning method as opposed to a flash method that has been used in similar research. The goal of this research is to improve performance of scanning LIDAR so it has better spatial resolution. The research in this thesis proves that incorporating 2-D imaging data into 3-D scanning LIDAR …

Examining Effectiveness Of Web-Based Internet Of Things Honeypots, Lukas A. Stafira

Theses and Dissertations

The Internet of Things (IoT) is growing at an alarming rate. It is estimated that there will be over 25 billion IoT devices by 2020. The simplicity of their function usually means that IoT devices have low processing power, which prevent them from having intricate security features, leading to vulnerabilities. This makes IoT devices the prime target of attackers in the coming years. Honeypots are intentionally vulnerable machines that run programs which appear as a vulnerable device to a would-be attacker. They are placed on a network to entice and trap an attacker and then gather information on them, including …

From Decoder Rings To Deep Fakes: Translating Complex Technologies For Legal Education, Rachel S. Evans, Jason Tubinis

Presentations

“Technological developments are disrupting the practice of law” is a common refrain, but the last few years has seen some particularly complex pieces of technology become the hot new thing in legal tech. This session will look at blockchain, quantum computing, artificial intelligence, and ‘Deep Fakes’ as examples of how librarians can stay abreast of technological developments and inform themselves about their impacts in the legal profession. Then we will look at how to translate the complexities and jargon of these examples into lessons for for-credit courses, one-off informational sessions, or meetings with stakeholders.

Graph-Based Temporal Analysis In Digital Forensics, Nikolai A. Adderley

Theses and Dissertations

Establishing a timeline as part of a digital forensics investigation is a vital part of understanding the order in which system events occurred. However, most digital forensics tools present timelines as histogram or as raw artifacts. Consequently, digital forensics examiners are forced to rely on manual, labor-intensive practices to reconstruct system events. Current digital forensics analysis tools are at their technological limit with the increasing storage and complexity of data. A graph-based timeline can present digital forensics evidence in a structure that can be immediately understood and effortlessly focused. This paper presents the Temporal Analysis Integration Management Application (TAIMA) to …

High Resolution Low-Bandwidth Real-Time Reconnaissance Using Structure From Motion With Planar Homography Estimation, Christian M.A. Arnold

Theses and Dissertations

Aerial real-time surveillance exists in a paradigm balancing the constraints of delivering high quality data and transporting data quickly. Typically, to have more of one, sacrifices must be made to the other. This is true of the environment in which an Unmanned Aerial Vehicle (UAV) operates, where real-time communication may be done through a low-bandwidth satellite connection resulting in low-resolution data, and serves as the primary limiting factor in all intelligence operations. Through the use of efficient computer vision techniques, we propose a new Structure from Motion (SfM) method capable of compressing high-resolution data, and delivering that data in real-time. …

Machine Learning Models Of C-17 Specific Range Using Flight Recorder Data, Marcus Catchpole

Theses and Dissertations

Fuel is a significant expense for the Air Force. The C-17 Globemaster eet accounts for a significant portion. Estimating the range of an aircraft based on its fuel consumption is nearly as old as flight itself. Consideration of operational energy and the related consideration of fuel efficiency is increasing. Meanwhile machine learning and data-mining techniques are on the rise. The old question, "How far can my aircraft y with a given load cargo and fuel?" has given way to "How little fuel can I load into an aircraft and safely arrive at the destination?" Specific range is a measure of …

Modeling A Consortium-Based Distributed Ledger Network With Applications For Intelligent Transportation Infrastructure, Luis A. Cintron

Theses and Dissertations

Emerging distributed-ledger networks are changing the landscape for environments of low trust among participating entities. Implementing such technologies in transportation infrastructure communications and operations would enable, in a secure fashion, decentralized collaboration among entities who do not fully trust each other. This work models a transportation records and events data collection system enabled by a Hyperledger Fabric blockchain network and simulated using a transportation environment modeling tool. A distributed vehicle records management use case is shown with the capability to detect and prevent unauthorized vehicle odometer tampering. Another use case studied is that of vehicular data collected during the event …

Instantaneous Bandwidth Expansion Using Software Defined Radios, Nicholas D. Everett

Theses and Dissertations

The Stimulated Unintended Radiated Emissions (SURE) process has been proven capable of classifying a device (e.g. a loaded antenna) as either operational or defective. Currently, the SURE process utilizes a specialized noise radar which is bulky, expensive and not easily supported. With current technology advancements, Software Defined Radios (SDRs) have become more compact, more readily available and significantly cheaper. The research here examines whether multiple SDRs can be integrated to replace the current specialized ultra-wideband noise radar used with the SURE process. The research specifically targets whether or not multiple SDR sub-band collections can be combined to form a wider …

Confidence Inference In Defensive Cyber Operator Decision Making, Graig S. Ganitano

Theses and Dissertations

Cyber defense analysts face the challenge of validating machine generated alerts regarding network-based security threats. Operations tempo and systematic manpower issues have increased the importance of these individual analyst decisions, since they typically are not reviewed or changed. Analysts may not always be confident in their decisions. If confidence can be accurately assessed, then analyst decisions made under low confidence can be independently reviewed and analysts can be offered decision assistance or additional training. This work investigates the utility of using neurophysiological and behavioral correlates of decision confidence to train machine learning models to infer confidence in analyst decisions. Electroencephalography …

Machine Translation With Image Context From Mandarin Chinese To English, Brooke E. Johnson

Theses and Dissertations

Despite ongoing improvements in machine translation, machine translators still lack the capability of incorporating context from which source text may have been derived. Machine translators use text from a source language to translate it into a target language without observing any visual context. This work aims to produce a neural machine translation model that is capable of accepting both text and image context as a multimodal translator from Mandarin Chinese to English. The model was trained on a small multimodal dataset of 700 images and sentences, and compared to a translator trained only on the text associated with those images. …

A Multi-Vehicle Cooperative Localization Approach For An Autonomy Framework, Edwin A. Mora

Theses and Dissertations

Offensive techniques produced by technological advancement present opportunities for adversaries to threaten the operational advantages of our joint and allied forces. Combating these new methodologies requires continuous and rapid development towards our own set of \game-changing" technologies. Through focused development of unmanned systems and autonomy, the Air Force can strive to maintain its technological superiority. Furthermore, creating a robust framework capable of testing and evaluating the principles that define autonomy allows for the exploration of future capabilities. This research presents development towards a hybrid reactive/deliberative architecture that will allow for the testing of the principles of task, cognitive, and peer …

A Blockchain-Based Anomalous Detection System For Internet Of Things Devices, Joshua K. Mosby

Theses and Dissertations

Internet of Things devices are highly susceptible to attack, and owners often fail to realize they have been compromised. This thesis describes an anomalous-based intrusion detection system that operates directly on Internet of Things devices utilizing a custom-built Blockchain. In this approach, an agent on each node compares the node's behavior to that of its peers, generating an alert if they are behaving differently. An experiment is conducted to determine the effectiveness at detecting malware. Three different code samples simulating common malware are deployed against a testbed of 12 Raspberry Pi devices. Increasing numbers are infected until two-thirds of the …

A Framework For Cyber Vulnerability Assessments Of Infiniband Networks, Daryl W. Schmitt

Theses and Dissertations

InfiniBand is a popular Input/Output interconnect technology used in High Performance Computing clusters. It is employed in over a quarter of the world’s 500 fastest computer systems. Although it was created to provide extremely low network latency with a high Quality of Service, the cybersecurity aspects of InfiniBand have yet to be thoroughly investigated. The InfiniBand Architecture was designed as a data center technology, logically separated from the Internet, so defensive mechanisms such as packet encryption were not implemented. Cyber communities do not appear to have taken an interest in InfiniBand, but that is likely to change as attackers branch …