Engineering Commons^™

Federated Agentless Detection Of Endpoints Using Behavioral And Characteristic Modeling, Hansaka Angel Dias Edirisinghe Kodituwakku

Doctoral Dissertations

During the past two decades computer networks and security have evolved that, even though we use the same TCP/IP stack, network traffic behaviors and security needs have significantly changed. To secure modern computer networks, complete and accurate data must be gathered in a structured manner pertaining to the network and endpoint behavior. Security operations teams struggle to keep up with the ever-increasing number of devices and network attacks daily. Often the security aspect of networks gets managed reactively instead of providing proactive protection. Data collected at the backbone are becoming inadequate during security incidents. Incident response teams require data that …

Profile-Guided Data Management For Heterogeneous Memory Systems, Matthew B. Olson

Doctoral Dissertations

Market forces and technological constraints have led to a gap between CPU and memory performance that has widened for decades. While processor scaling has plateaued in recent years, this gap persists and is not expected to diminish for the foreseeable future. This discrepancy presents a host of challenges for scaling application performance, which have only been exacerbated in recent years, as increasing demands for fast and effective data analytics are driving memory energy, bandwidth, and capacity requirements to new heights.

To address these trends, hardware architects have introduced a plethora of memory technologies. For example, most modern memory systems include …

Qualitative And Quantitative Improvements For Positron Emission Tomography Using Different Motion Correction Methodologies, Tasmia Rahman Tumpa

Doctoral Dissertations

Positron Emission Tomography (PET) data suffers from low image quality and quantitative accuracy due to different kinds of motion of patients during imaging. Hardware-based motion correction is currently the standard; however, is limited by several constraints, the most important of which is retroactive data correction. Data-driven techniques to perform motion correction in this regard are active areas of research. The motivation behind this work lies in developing a complete data-driven approach to address both motion detection and correction. The work first presents an algorithm based on the positron emission particle tracking (PEPT) technique and makes use of time-of-flight (TOF) information …

On Improving Robustness Of Hardware Security Primitives And Resistance To Reverse Engineering Attacks, Vinay C. Patil

Doctoral Dissertations

The continued growth of information technology (IT) industry and proliferation of interconnected devices has aggravated the problem of ensuring security and necessitated the need for novel, robust solutions. Physically unclonable functions (PUFs) have emerged as promising secure hardware primitives that can utilize the disorder introduced during manufacturing process to generate unique keys. They can be utilized as \textit{lightweight} roots-of-trust for use in authentication and key generation systems. Unlike insecure non-volatile memory (NVM) based key storage systems, PUFs provide an advantage -- no party, including the manufacturer, should be able to replicate the physical disorder and thus, effectively clone the PUF. …

Resource Allocation In Distributed Service Networks, Nitish Kumar Panigrahy

Doctoral Dissertations

The past few years have witnessed significant growth in the use of distributed network analytics involving agile code, data and computational resources. In many such networked systems, for example, Internet of Things (IoT), a large number of smart devices, sensors, processing and storage resources are widely distributed in a geographic region. These devices and resources distributed over a physical space are collectively called a distributed service network. Efficient resource allocation in such high performance service networks remains one of the most critical problems. In this thesis, we model and optimize the allocation of resources in a distributed service network. This …

Cost-Efficient Resource Provisioning For Cloud-Enabled Schedulers, Lurdh Pradeep Reddy Ambati

Doctoral Dissertations

Since the last decade, public cloud platforms are rapidly becoming de-facto computing platform for our society. To support the wide range of users and their diverse applications, public cloud platforms started to offer the same VMs under many purchasing options that differ across their cost, performance, availability, and time commitments. Popular purchasing options include on-demand, reserved, and transient VM types. Reserved VMs require long time commitments, whereas users can acquire and release the on-demand (and transient) VMs at any time. While transient VMs cost significantly less than on-demand VMs, platforms may revoke them at any time. In general, the stronger …

Sensor Fusion For Object Detection And Tracking In Autonomous Vehicles, Mohamad Ramin Nabati

Doctoral Dissertations

Autonomous driving vehicles depend on their perception system to understand the environment and identify all static and dynamic obstacles surrounding the vehicle. The perception system in an autonomous vehicle uses the sensory data obtained from different sensor modalities to understand the environment and perform a variety of tasks such as object detection and object tracking. Combining the outputs of different sensors to obtain a more reliable and robust outcome is called sensor fusion. This dissertation studies the problem of sensor fusion for object detection and object tracking in autonomous driving vehicles and explores different approaches for utilizing deep neural networks …

Toward Reliable And Efficient Message Passing Software For Hpc Systems: Fault Tolerance And Vector Extension, Dong Zhong

Doctoral Dissertations

As the scale of High-performance Computing (HPC) systems continues to grow, researchers are devoted themselves to achieve the best performance of running long computing jobs on these systems. My research focus on reliability and efficiency study for HPC software.

First, as systems become larger, mean-time-to-failure (MTTF) of these HPC systems is negatively impacted and tends to decrease. Handling system failures becomes a prime challenge. My research aims to present a general design and implementation of an efficient runtime-level failure detection and propagation strategy targeting large-scale, dynamic systems that is able to detect both node and process failures. Using multiple overlapping …

Human Fatigue Predictions In Complex Aviation Crew Operational Impact Conditions, Suresh Rangan

Doctoral Dissertations

In this last decade, several regulatory frameworks across the world in all modes of transportation had brought fatigue and its risk management in operations to the forefront. Of all transportation modes air travel has been the safest means of transportation. Still as part of continuous improvement efforts, regulators are insisting the operators to adopt strong fatigue science and its foundational principles to reinforce safety risk assessment and management. Fatigue risk management is a data driven system that finds a realistic balance between safety and productivity in an organization. This work discusses the effects of mathematical modeling of fatigue and its …

Towards Secure Deep Neural Networks For Cyber-Physical Systems, Jiangnan Li

Doctoral Dissertations

In recent years, deep neural networks (DNNs) are increasingly investigated in the literature to be employed in cyber-physical systems (CPSs). DNNs own inherent advantages in complex pattern identifying and achieve state-of-the-art performances in many important CPS applications. However, DNN-based systems usually require large datasets for model training, which introduces new data management issues. Meanwhile, research in the computer vision domain demonstrated that the DNNs are highly vulnerable to adversarial examples. Therefore, the security risks of employing DNNs in CPSs applications are of concern.

In this dissertation, we study the security of employing DNNs in CPSs from both the data domain …

Utility Scale Building Energy Modeling And Climate Impacts, Brett C. Bass

Doctoral Dissertations

Energy consumption is steadily increasing year over year in the United States (US). Climate change and anthropogenically forced shifts in weather have a significant impact on energy use as well as the resilience of the built environment and the electric grid. With buildings accounting for about 40% of total energy use in the US, building energy modeling (BEM) at a large scale is critical. This work advances that effort in a number of ways. First, current BEM approaches, their ability to scale to large geographical areas, and global climate models are reviewed. Next, a methodology for large-scale BEM is illustrated, …

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 …

Addressing Security Challenges In Embedded Systems And Multi-Tenant Fpgas, Georgios Provelengios

Doctoral Dissertations

Embedded systems and field-programmable gate arrays (FPGAs) have become crucial parts of the infrastructure that supports our modern technological world. Given the multitude of threats that are present, the need for secure computing systems is undeniably greater than ever. Embedded systems and FPGAs are governed by characteristics that create unique security challenges and vulnerabilities. Despite their array of uses, embedded systems are often built with modest microprocessors that do not support the conventional security solutions used by workstations, such as virus scanners. In the first part of this dissertation, a microprocessor defense mechanism that uses a hardware monitor to protect …

Scheduling Based Optimization In Software Defined Radio And Wireless Networks, Nathan Daniel Price

Doctoral Dissertations

"The objective of this work is to enable dynamic sharing of software-defined radio (SDR) transceivers through the concepts of hardware virtualization and real-time resource management. SDR is a way to build a digital radio that consists of a software back-end for digital signal processing (DSP) and an analog front-end transceiver for waveform generation and reception. This work proposes the use of a virtualization layer to decouple back-end SDR software from front-end transceivers. With this arrangement, front-ends are said to be virtualized, and it becomes possible to share a limited number of front-ends among many SDR back-ends through different multiplexing techniques. …

Instrumentation, Modeling, And Sound Metamodeling Foundations For Complex Hybrid Systems, Natasha Amelia Jarus

Doctoral Dissertations

Many of our critical infrastructures, from power grids to water distribution networks, are complex hybrid systems that use software to control their non-trivial physical dynamics. These systems must be able to capably serve their purpose, while also being reliable, dependable, safe, secure, and efficient. Representation and analysis of these features requires the creation of several distinct models. These models may encode design goals or be derived from collected instrumentation data, reflecting both how a system ought to operate and how it does operate. It is essential to ensure that all of these models consistently and accurately describe the same system. …