Computer Sciences Commons^™

Comparing Phishing Training And Campaign Methods For Mitigating Malicious Emails In Organizations, Jackie Christopher Scott

CCE Theses and Dissertations

Although there have been numerous technological advancements in the last several years, there continues to be a real threat as it pertains to social engineering, especially phishing, spear-phishing, and Business Email Compromise (BEC). While the technologies to protect corporate employees and network borders have gotten better, there are still human elements to consider. No technology can protect an organization completely, so it is imperative that end users are provided with the most up-to-date and relevant Security Education, Training, and Awareness (SETA). Phishing, spear-phishing, and BEC are three primary vehicles used by attackers to infiltrate corporate networks and manipulate end users …

Increasing Code Completion Accuracy In Pythia Models For Non-Standard Python Libraries, David Buksbaum

CCE Theses and Dissertations

Contemporary software development with modern programming languages leverages Integrated Development Environments, smart text editors, and similar tooling with code completion capabilities to increase the efficiency of software developers. Recent code completion research has shown that the combination of natural language processing with recurrent neural networks configured with long short-term memory can improve the accuracy of code completion predictions over prior models. It is well known that the accuracy of predictive systems based on training data is correlated to the quality and the quantity of the training data. This dissertation demonstrates that by expanding the training data set to include more …

An Empirical Assessment Of The Use Of Password Workarounds And The Cybersecurity Risk Of Data Breaches, Michael Joseph Rooney

CCE Theses and Dissertations

Passwords have been used for a long time to grant controlled access to classified spaces, electronics, networks, and more. However, the dramatic increase in user accounts over the past few decades has exposed the realization that technological measures alone cannot ensure a high level of IS security; this leaves the end-users holding a critical role in protecting their organization and personal information. The increased use of IS as a working tool for employees increases the number of accounts and passwords required. Despite being more aware of password entropy, users still often participate in deviant password behaviors, known as ‘password workarounds’ …

Optimizing Constraint Selection In A Design Verification Environment For Efficient Coverage Closure, Vanessa Cooper

CCE Theses and Dissertations

No abstract provided.

Integrating The Spatial Pyramid Pooling Into 3d Convolutional Neural Networks For Cerebral Microbleeds Detection, Andre Accioly Veira

CCE Theses and Dissertations

Cerebral microbleeds (CMB) are small foci of chronic blood products in brain tissues that are critical markers for cerebral amyloid angiopathy. CMB increases the risk of symptomatic intracerebral hemorrhage and ischemic stroke. CMB can also cause structural damage to brain tissues resulting in neurologic dysfunction, cognitive impairment, and dementia. Due to the paramagnetic properties of blood degradation products, CMB can be better visualized via susceptibility-weighted imaging (SWI) than magnetic resonance imaging (MRI).CMB identification and classification have been based mainly on human visual identification of SWI features via shape, size, and intensity information. However, manual interpretation can be biased. Visual screening …

A Study Of The Effect Of Types Of Organizational Culture On Information Security Procedural Countermeasures, Sheri James

CCE Theses and Dissertations

This study examined the impact of specific organizational cultures on information security procedural countermeasures (ISPC). With increasing security incidents and data breaches, organizations acknowledge that people are their greatest asset as well as a vulnerability. Previous research into information security procedural controls has centered on behavioral, cognitive, and social theories; some literature incorporates general notions of organization culture yet there is still an absence in socio-organizational studies dedicated to elucidating how information security policy (ISP) compliance can be augmented by implementing comprehensive security education, training, and awareness (SETA) programs focusing on education, training, and awareness initiatives.

A theoretical model was …

Adversarial Training Of Deep Neural Networks, Anabetsy Termini

CCE Theses and Dissertations

Deep neural networks used for image classification are highly susceptible to adversarial attacks. The de facto method to increase adversarial robustness is to train neural networks with a mixture of adversarial images and unperturbed images. However, this method leads to robust overfitting, where the network primarily learns to recognize one specific type of attack used to generate the images while remaining vulnerable to others after training. In this dissertation, we performed a rigorous study to understand whether combinations of state of the art data augmentation methods with Stochastic Weight Averaging improve adversarial robustness and diminish adversarial overfitting across a wide …

Application Of Genomic Compression Techniques For Efficient Storage Of Captured Network Traffic Packets, James Alfred Loving

CCE Theses and Dissertations

In cybersecurity, one of most important forensic tools are audit files; they contain a record of cyber events that occur on systems throughout the enterprise. Threats to an enterprise have become one of the top concerns of IT professionals world-wide. Although there are various approaches to detect anomalous insider behavior, these approaches are not always able to detect advanced persistent threats or even exfiltration of sensitive data by insiders. The issue is the volume of network data required to identify this anomalous activity. It has been estimated that an average corporate user creates a minimum of 1.5 MB audit data …

An Investigation Of Methods For Improving Spatial Invariance Of Convolutional Neural Networks For Image Classification, David Noel

CCE Theses and Dissertations

Convolutional Neural Networks (CNNs) have achieved impressive results on complex visual tasks such as image recognition. They are commonly assumed to be spatially invariant to small transformations of their input images. Spatial invariance is a fundamental property that characterizes how a model reacts to input transformations, i.e., its generalizability - and deep networks that can robustly classify objects placed in different orientations or lighting conditions have the property of invariance. However, several authors have recently shown that this is not the case, and that slight rotations, translations, or rescaling of their input images significantly reduce the network’s predictive accuracy. Furthermore, …