Computer Engineering Commons^™

An Analysis Of Modern Password Manager Security And Usage On Desktop And Mobile Devices, Timothy Oesch

Doctoral Dissertations

Security experts recommend password managers to help users generate, store, and enter strong, unique passwords. Prior research confirms that managers do help users move towards these objectives, but it also identified usability and security issues that had the potential to leak user data or prevent users from making full use of their manager. In this dissertation, I set out to measure to what extent modern managers have addressed these security issues on both desktop and mobile environments. Additionally, I have interviewed individuals to understand their password management behavior.

I begin my analysis by conducting the first security evaluation of the …

Leveraging Conventional Internet Routing Protocol Behavior To Defeat Ddos And Adverse Networking Conditions, Jared M. Smith

Doctoral Dissertations

The Internet is a cornerstone of modern society. Yet increasingly devastating attacks against the Internet threaten to undermine the Internet's success at connecting the unconnected. Of all the adversarial campaigns waged against the Internet and the organizations that rely on it, distributed denial of service, or DDoS, tops the list of the most volatile attacks. In recent years, DDoS attacks have been responsible for large swaths of the Internet blacking out, while other attacks have completely overwhelmed key Internet services and websites. Core to the Internet's functionality is the way in which traffic on the Internet gets from one destination …

Achieving High Reliability And Efficiency In Maintaining Large-Scale Storage Systems Through Optimal Resource Provisioning And Data Placement, Lipeng Wan

Doctoral Dissertations

With the explosive increase in the amount of data being generated by various applications, large-scale distributed and parallel storage systems have become common data storage solutions and been widely deployed and utilized in both industry and academia. While these high performance storage systems significantly accelerate the data storage and retrieval, they also bring some critical issues in system maintenance and management. In this dissertation, I propose three methodologies to address three of these critical issues.

First, I develop an optimal resource management and spare provisioning model to minimize the impact brought by component failures and ensure a highly operational experience …

Neuron Clustering For Mitigating Catastrophic Forgetting In Supervised And Reinforcement Learning, Benjamin Frederick Goodrich

Doctoral Dissertations

Neural networks have had many great successes in recent years, particularly with the advent of deep learning and many novel training techniques. One issue that has affected neural networks and prevented them from performing well in more realistic online environments is that of catastrophic forgetting. Catastrophic forgetting affects supervised learning systems when input samples are temporally correlated or are non-stationary. However, most real-world problems are non-stationary in nature, resulting in prolonged periods of time separating inputs drawn from different regions of the input space.

Reinforcement learning represents a worst-case scenario when it comes to precipitating catastrophic forgetting in neural networks. …

Computational Framework For Small Animal Spect Imaging: Simulation And Reconstruction, Sang Hyeb Lee

Doctoral Dissertations

Small animal Single Photon Emission Computed Tomography (SPECT) has been an invaluable asset in biomedical science since this non-invasive imaging technique allows the longitudinal studies of animal models of human diseases. However, the image degradation caused by non-stationary collimator-detector response and single photon emitting nature of SPECT makes it difficult to provide a quantitative measure of 3D radio-pharmaceutical distribution inside the patient. Moreover, this problem exacerbates when an intra-peritoneal X-ray contrast agent is injected into a mouse for low-energy radiotracers.

In this dissertation, we design and develop a complete computational framework for the entire SPECT scan procedure from the radio-pharmaceutical …

3d Robotic Sensing Of People: Human Perception, Representation And Activity Recognition, Hao Zhang

Doctoral Dissertations

The robots are coming. Their presence will eventually bridge the digital-physical divide and dramatically impact human life by taking over tasks where our current society has shortcomings (e.g., search and rescue, elderly care, and child education). Human-centered robotics (HCR) is a vision to address how robots can coexist with humans and help people live safer, simpler and more independent lives.

As humans, we have a remarkable ability to perceive the world around us, perceive people, and interpret their behaviors. Endowing robots with these critical capabilities in highly dynamic human social environments is a significant but very challenging problem in practical …

Online Multi-Stage Deep Architectures For Feature Extraction And Object Recognition, Derek Christopher Rose

Doctoral Dissertations

Multi-stage visual architectures have recently found success in achieving high classification accuracies over image datasets with large variations in pose, lighting, and scale. Inspired by techniques currently at the forefront of deep learning, such architectures are typically composed of one or more layers of preprocessing, feature encoding, and pooling to extract features from raw images. Training these components traditionally relies on large sets of patches that are extracted from a potentially large image dataset. In this context, high-dimensional feature space representations are often helpful for obtaining the best classification performances and providing a higher degree of invariance to object transformations. …

Exploring Computational Chemistry On Emerging Architectures, David Dewayne Jenkins

Doctoral Dissertations

Emerging architectures, such as next generation microprocessors, graphics processing units, and Intel MIC cards, are being used with increased popularity in high performance computing. Each of these architectures has advantages over previous generations of architectures including performance, programmability, and power efficiency. With the ever-increasing performance of these architectures, scientific computing applications are able to attack larger, more complicated problems. However, since applications perform differently on each of the architectures, it is difficult to determine the best tool for the job. This dissertation makes the following contributions to computer engineering and computational science. First, this work implements the computational chemistry variational …

Parallel For Loops On Heterogeneous Resources, Frederick Edward Weber

Doctoral Dissertations

In recent years, Graphics Processing Units (GPUs) have piqued the interest of researchers in scientific computing. Their immense floating point throughput and massive parallelism make them ideal for not just graphical applications, but many general algorithms as well. Load balancing applications and taking advantage of all computational resources in a machine is a difficult challenge, especially when the resources are heterogeneous. This dissertation presents the clUtil library, which vastly simplifies developing OpenCL applications for heterogeneous systems. The core focus of this dissertation lies in clUtil's ParallelFor construct and our novel PINA scheduler which can efficiently load balance work onto multiple …

Dynamic Task Execution On Shared And Distributed Memory Architectures, Asim Yarkhan

Doctoral Dissertations

Multicore architectures with high core counts have come to dominate the world of high performance computing, from shared memory machines to the largest distributed memory clusters. The multicore route to increased performance has a simpler design and better power efficiency than the traditional approach of increasing processor frequencies. But, standard programming techniques are not well adapted to this change in computer architecture design.

In this work, we study the use of dynamic runtime environments executing data driven applications as a solution to programming multicore architectures. The goals of our runtime environments are productivity, scalability and performance. We demonstrate productivity by …