Computer Engineering Commons^™

Towards A Robust Defense: A Multifaceted Approach To The Detection And Mitigation Of Neural Backdoor Attacks Through Feature Space Exploration And Analysis, Liuwan Zhu

Electrical & Computer Engineering Theses & Dissertations

From voice assistants to self-driving vehicles, machine learning(ML), especially deep learning, revolutionizes the way we work and live, through the wide adoption in a broad range of applications. Unfortunately, this widespread use makes deep learning-based systems a desirable target for cyberattacks, such as generating adversarial examples to fool a deep learning system to make wrong decisions. In particular, many recent studies have revealed that attackers can corrupt the training of a deep learning model, e.g., through data poisoning, or distribute a deep learning model they created with “backdoors” planted, e.g., distributed as part of a software library, so that the …

Wearable Sensor Gait Analysis For Fall Detection Using Deep Learning Methods, Haben Girmay Yhdego

Electrical & Computer Engineering Theses & Dissertations

World Health Organization (WHO) data show that around 684,000 people die from falls yearly, making it the second-highest mortality rate after traffic accidents [1]. Early detection of falls, followed by pneumatic protection, is one of the most effective means of ensuring the safety of the elderly. In light of the recent widespread adoption of wearable sensors, it has become increasingly critical that fall detection models are developed that can effectively process large and sequential sensor signal data. Several researchers have recently developed fall detection algorithms based on wearable sensor data. However, real-time fall detection remains challenging because of the wide …

Cyber Resilience Analytics For Cyber-Physical Systems, Md Ariful Haque

Electrical & Computer Engineering Theses & Dissertations

Cyber-physical systems (CPSs) are complex systems that evolve from the integrations of components dealing with physical processes and real-time computations, along with networking. CPSs often incorporate approaches merging from different scientific fields such as embedded systems, control systems, operational technology, information technology systems (ITS), and cybernetics. Today critical infrastructures (CIs) (e.g., energy systems, electric grids, etc.) and other CPSs (e.g., manufacturing industries, autonomous transportation systems, etc.) are experiencing challenges in dealing with cyberattacks. Major cybersecurity concerns are rising around CPSs because of their ever-growing use of information technology based automation. Often the security concerns are limited to probability-based possible attack …

Applied Deep Learning: Case Studies In Computer Vision And Natural Language Processing, Md Reshad Ul Hoque

Electrical & Computer Engineering Theses & Dissertations

Deep learning has proved to be successful for many computer vision and natural language processing applications. In this dissertation, three studies have been conducted to show the efficacy of deep learning models for computer vision and natural language processing. In the first study, an efficient deep learning model was proposed for seagrass scar detection in multispectral images which produced robust, accurate scars mappings. In the second study, an arithmetic deep learning model was developed to fuse multi-spectral images collected at different times with different resolutions to generate high-resolution images for downstream tasks including change detection, object detection, and land cover …

Joint Linear And Nonlinear Computation With Data Encryption For Efficient Privacy-Preserving Deep Learning, Qiao Zhang

Electrical & Computer Engineering Theses & Dissertations

Deep Learning (DL) has shown unrivalled performance in many applications such as image classification, speech recognition, anomalous detection, and business analytics. While end users and enterprises own enormous data, DL talents and computing power are mostly gathered in technology giants having cloud servers. Thus, data owners, i.e., the clients, are motivated to outsource their data, along with computationally-intensive tasks, to the server in order to leverage the server’s abundant computation resources and DL talents for developing cost-effective DL solutions. However, trust is required between the server and the client to finish the computation tasks (e.g., conducting inference for the newly-input …

Electrostatic Design And Characterization Of A 200 Kev Photogun And Wien Spin Rotator, Gabriel G. Palacios Serrano

Electrical & Computer Engineering Theses & Dissertations

High-energy nuclear physics experiments at the Jefferson Lab Continuous Electron Beam Accelerator Facility (CEBAF) require high spin-polarization electron beams produced from strained super-lattice GaAs photocathodes activated to negative electron affinity in a high voltage photogun operating at 130 kV dc. A pair of Wien filter spin rotators in the injector provides precise control of the electron beam polarization at the end station target. An upgrade of the CEBAF injector to better support the upcoming Moller experiment requires increasing the electron beam energy to 200 keV, resulting in better transmission through injector apertures and improved photocathode lifetime. In addition, the energy …

Secure Mobile Computing By Using Convolutional And Capsule Deep Neural Networks, Rui Ning

Electrical & Computer Engineering Theses & Dissertations

Mobile devices are becoming smarter to satisfy modern user's increasing needs better, which is achieved by equipping divers of sensors and integrating the most cutting-edge Deep Learning (DL) techniques. As a sophisticated system, it is often vulnerable to multiple attacks (side-channel attacks, neural backdoor, etc.). This dissertation proposes solutions to maintain the cyber-hygiene of the DL-Based smartphone system by exploring possible vulnerabilities and developing countermeasures.

First, I actively explore possible vulnerabilities on the DL-Based smartphone system to develop proactive defense mechanisms. I discover a new side-channel attack on smartphones using the unrestricted magnetic sensor data. I demonstrate that attackers can …

Deep Cellular Recurrent Neural Architecture For Efficient Multidimensional Time-Series Data Processing, Lasitha S. Vidyaratne

Electrical & Computer Engineering Theses & Dissertations

Efficient processing of time series data is a fundamental yet challenging problem in pattern recognition. Though recent developments in machine learning and deep learning have enabled remarkable improvements in processing large scale datasets in many application domains, most are designed and regulated to handle inputs that are static in time. Many real-world data, such as in biomedical, surveillance and security, financial, manufacturing and engineering applications, are rarely static in time, and demand models able to recognize patterns in both space and time. Current machine learning (ML) and deep learning (DL) models adapted for time series processing tend to grow in …

Cyber Security- A New Secured Password Generation Algorithm With Graphical Authentication And Alphanumeric Passwords Along With Encryption, Akash Rao

Electrical & Computer Engineering Theses & Dissertations

Graphical passwords are always considered as an alternative of alphanumeric passwords for their better memorability and usability [1]. Alphanumeric passwords provide an adequate amount of satisfaction, but they do not offer better memorability compared to graphical passwords [1].

On the other hand, graphical passwords are considered less secured and provide better memorability [1]. Therefore many researchers have researched on graphical passwords to overcome the vulnerability. One of the most significant weaknesses of the graphical passwords is "Shoulder Surfing Attack," which means, sneaking into a victim's computer to learn the whole password or part of password or some confidential information. Such …

Deep Recurrent Learning For Efficient Image Recognition Using Small Data, Mahbubul Alam

Electrical & Computer Engineering Theses & Dissertations

Recognition is fundamental yet open and challenging problem in computer vision. Recognition involves the detection and interpretation of complex shapes of objects or persons from previous encounters or knowledge. Biological systems are considered as the most powerful, robust and generalized recognition models. The recent success of learning based mathematical models known as artificial neural networks, especially deep neural networks, have propelled researchers to utilize such architectures for developing bio-inspired computational recognition models. However, the computational complexity of these models increases proportionally to the challenges posed by the recognition problem, and more importantly, these models require a large amount of data …

Speech Based Machine Learning Models For Emotional State Recognition And Ptsd Detection, Debrup Banerjee

Electrical & Computer Engineering Theses & Dissertations

Recognition of emotional state and diagnosis of trauma related illnesses such as posttraumatic stress disorder (PTSD) using speech signals have been active research topics over the past decade. A typical emotion recognition system consists of three components: speech segmentation, feature extraction and emotion identification. Various speech features have been developed for emotional state recognition which can be divided into three categories, namely, excitation, vocal tract and prosodic. However, the capabilities of different feature categories and advanced machine learning techniques have not been fully explored for emotion recognition and PTSD diagnosis. For PTSD assessment, clinical diagnosis through structured interviews is a …

Computational Modeling Of Facial Response For Detecting Differential Traits In Autism Spectrum Disorders, Manar D. Samad

Electrical & Computer Engineering Theses & Dissertations

This dissertation proposes novel computational modeling and computer vision methods for the analysis and discovery of differential traits in subjects with Autism Spectrum Disorders (ASD) using video and three-dimensional (3D) images of face and facial expressions. ASD is a neurodevelopmental disorder that impairs an individual’s nonverbal communication skills. This work studies ASD from the pathophysiology of facial expressions which may manifest atypical responses in the face. State-of-the-art psychophysical studies mostly employ na¨ıve human raters to visually score atypical facial responses of individuals with ASD, which may be subjective, tedious, and error prone. A few quantitative studies use intrusive sensors on …

High Dimensional Data Set Analysis Using A Large-Scale Manifold Learning Approach, Loc Tran

Electrical & Computer Engineering Theses & Dissertations

Because of technological advances, a trend occurs for data sets increasing in size and dimensionality. Processing these large scale data sets is challenging for conventional computers due to computational limitations. A framework for nonlinear dimensionality reduction on large databases is presented that alleviates the issue of large data sets through sampling, graph construction, manifold learning, and embedding. Neighborhood selection is a key step in this framework and a potential area of improvement. The standard approach to neighborhood selection is setting a fixed neighborhood. This could be a fixed number of neighbors or a fixed neighborhood size. Each of these has …

Idpal – A Partially-Adiabatic Energy-Efficient Logic Family: Theory And Applications To Secure Computing, Mihail T. Cutitaru

Electrical & Computer Engineering Theses & Dissertations

Low-power circuits and issues associated with them have gained a significant amount of attention in recent years due to the boom in portable electronic devices. Historically, low-power operation relied heavily on technology scaling and reduced operating voltage, however this trend has been slowing down recently due to the increased power density on chips. This dissertation introduces a new very-low power partially-adiabatic logic family called Input-Decoupled Partially-Adiabatic Logic (IDPAL) with applications in low-power circuits. Experimental results show that IDPAL reduces energy usage by 79% compared to equivalent CMOS implementations and by 25% when compared to the best adiabatic implementation. Experiments ranging …

Transparent Spectrum Co-Access In Cognitive Radio Networks, Jonathan Daniel Backens

Electrical & Computer Engineering Theses & Dissertations

The licensed wireless spectrum is currently under-utilized by as much as 85%. Cognitive radio networks have been proposed to employ dynamic spectrum access to share this under-utilized spectrum between licensed primary user transmissions and unlicensed secondary user transmissions. Current secondary user opportunistic spectrum access methods, however, remain limited in their ability to provide enough incentive to convince primary users to share the licensed spectrum, and they rely on primary user absence to guarantee secondary user performance. These challenges are addressed by developing a Dynamic Spectrum Co-Access Architecture (DSCA) that allows secondary user transmissions to co-access transparently and concurrently with primary …

A Vision-Based Automatic Safe Landing-Site Detection System, Yufei Shen

Electrical & Computer Engineering Theses & Dissertations

An automatic safe landing-site detection system is proposed for aircraft emergency landing, based on visible information acquired by aircraft-mounted cameras. Emergency landing is an unplanned event in response to emergency situations. If, as is unfortunately usually the case, there is no airstrip or airfield that can be reached by the un-powered aircraft, a crash landing or ditching has to be carried out. Identifying a safe landing-site is critical to the survival of passengers and crew. Conventionally, the pilot chooses the landing-site visually by looking at the terrain through the cockpit. The success of this vital decision greatly depends on the …

Image-Guided Robotic Dental Implantation With Natural-Root-Formed Implants, Xiaoyan Sun

Electrical & Computer Engineering Theses & Dissertations

Dental implantation is now recognized as the standard of the care for tooth replacement. Although many studies show high short term survival rates greater than 95%, long term studies (> 5 years) have shown success rates as low as 41.9%. Reasons affecting the long term success rates might include surgical factors such as limited accuracy of implant placement, lack of spacing controls, and overheating during the placement.

In this dissertation, a comprehensive solution for improving the outcome of current dental implantation is presented, which includes computer-aided preoperative planning for better visualization of patient-specific information and automated robotic site-preparation for superior …

An Efficient Boosted Classifier Tree-Based Feature Point Tracking System For Facial Expression Analysis, Adam Redd Livingston

Electrical & Computer Engineering Theses & Dissertations

The study of facial movement and expression has been a prominent area of research since the early work of Charles Darwin. The Facial Action Coding System (FACS), developed by Paul Ekman, introduced the first universal method of coding and measuring facial movement. Human-Computer Interaction seeks to make human interaction with computer systems more effective, easier, safer, and more seamless. Facial expression recognition can be broken down into three distinctive subsections: Facial Feature Localization, Facial Action Recognition, and Facial Expression Classification. The first and most important stage in any facial expression analysis system is the localization of key facial features. Localization …

Design Of Multi Agent Based Crowd Injury Model, Emin Kugu

Electrical & Computer Engineering Theses & Dissertations

A major concern of many government agencies is to predict and control the behavior of crowds in different situations. Many times such gatherings are legal, legitimate, and peaceful. But there are times when they can turn violent, run out of control, result in material damages and even casualties. It then becomes the duty of governments to bring them under control using a variety of techniques, including non-lethal and lethal weapons, if necessary.

In order to aid decision makers on the course of action in crowd control, there are modeling and simulation tools that can provide guidelines by giving programmed rules …

Transmitter Optimization In Multiuser Wireless Systems With Quality Of Service Constraints, Danda B. Rawat

Electrical & Computer Engineering Theses & Dissertations

In this dissertation, transmitter adaptation for optimal resource allocation in wireless communication systems are investigated. First, a multiple access channel model is considered where many transmitters communicate with a single receiver. This scenario is a basic component of a. wireless network in which multiple users simultaneously access the resources of a wireless service provider. Adaptive algorithms for transmitter optimization to meet Quality-of-Service (QoS) requirements in a distributed manner are studied. Second, an interference channel model is considered where multiple interfering transmitter-receiver pairs co-exist such that a given transmitter communicates with its intended receiver in the presence of interference from other …

Tree-D-Seek: A Framework For Retrieving Three-Dimensional Scenes, Saurav Mazumdar

Electrical & Computer Engineering Theses & Dissertations

In this dissertation, a strategy and framework for retrieving 3D scenes is proposed. The strategy is to retrieve 3D scenes based on a unified approach for indexing content from disparate information sources and information levels. The TREE-D-SEEK framework implements the proposed strategy for retrieving 3D scenes and is capable of indexing content from a variety of corpora at distinct information levels. A semantic annotation model for indexing 3D scenes in the TREE-D-SEEK framework is also proposed. The semantic annotation model is based on an ontology for rapid prototyping of 3D virtual worlds.

With ongoing improvements in computer hardware and 3D …

High-Performance Broadcast And Multicast Protocols For Multi-Radio Multi-Channel Wireless Mesh Networks, Jun Wang

Electrical & Computer Engineering Theses & Dissertations

Recently, wireless mesh networks (WMNs) have attracted much attention. A vast amount of unicast, multicast and broadcast protocols has been developed for WMNs or mobile ad hoc networks (MANETs). First of all, broadcast and multicast in wireless networks are fundamentally different from the way in which wired networks function due to the well-known wireless broadcast/multicast advantage. Moreover, most broadcast and multicast protocols in wireless networks assume a single-radio single-channel and single-rate network model, or a generalized physical model, which does not take into account the impact of interference. This dissertation focuses on high-performance broadcast and multicast protocols designed for multi-radio …

A Subspace Projection Methodology For Nonlinear Manifold Based Face Recognition, Praveen Sankaran

Electrical & Computer Engineering Theses & Dissertations

A novel feature extraction method that utilizes nonlinear mapping from the original data space to the feature space is presented in this dissertation. Feature extraction methods aim to find compact representations of data that are easy to classify. Measurements with similar values are grouped to same category, while those with differing values are deemed to be of separate categories. For most practical systems, the meaningful features of a pattern class lie in a low dimensional nonlinear constraint region (manifold) within the high dimensional data space. A learning algorithm to model this nonlinear region and to project patterns to this feature …

Supporting Protocols For Structuring And Intelligent Information Dissemination In Vehicular Ad Hoc Networks, Filip Cuckov

Electrical & Computer Engineering Theses & Dissertations

The goal of this dissertation is the presentation of supporting protocols for structuring and intelligent data dissemination in vehicular ad hoc networks (VANETs). The protocols are intended to first introduce a structure in VANETs, and thus promote the spatial reuse of network resources. Segmenting a flat VANET in multiple cluster structures allows for more efficient use of the available bandwidth, which can effectively increase the capacity of the network. The cluster structures can also improve the scalability of the underlying communication protocols. The structuring and maintenance of the network introduces additional overhead. The aim is to provide a mechanism for …

Robust Face Representation And Recognition Under Low Resolution And Difficult Lighting Conditions, Mohammad Moinul Islam

Electrical & Computer Engineering Theses & Dissertations

This dissertation focuses on different aspects of face image analysis for accurate face recognition under low resolution and poor lighting conditions. A novel resolution enhancement technique is proposed for enhancing a low resolution face image into a high resolution image for better visualization and improved feature extraction, especially in a video surveillance environment. This method performs kernel regression and component feature learning in local neighborhood of the face images. It uses directional Fourier phase feature component to adaptively lean the regression kernel based on local covariance to estimate the high resolution image. For each patch in the neighborhood, four directional …

A Formal Object Model For Layered Networks To Support Verification And Simulation, Rasha M. B. E. Morsi

Electrical & Computer Engineering Theses & Dissertations

This work presents an abstract formal model of the interconnection structure of the Open Systems Interconnection Reference Model (OSI-RM) developed using Object-Oriented modeling principles permitting it to serve as a re-usable platform in supporting the development of simulations and formal methods applied to layered network protocols. A simulation of the object model using MODSIM III was developed and Prototype Verification System (PVS) was used to show the applicability of the object model to formal methods by formally specifying and verifying a Global Systems for Mobile communications (GSM) protocol. This application has proved to be successful in two aspects. The first …

The Cluster Multipole Algorithm For Far-Field Computations, Rakesh R. Patel

Electrical & Computer Engineering Theses & Dissertations

Computer simulations of N-body systems are beneficial to study the overall behavior of a number of physical systems in fields such as astrophysics, molecular dynamics, and computational fluid dynamics. A new approach for computer simulations of N-body systems is proposed in this research. The new algorithm is called the Cluster Multipole Algorithm (CMA). The goals of the new algorithm are to improve the applicability to non-point sources and to provide more control on the accuracy over current algorithms. The algorithm is targeted to applications that do not require rebuilding the data structure about the system every time step due to …