Physical Sciences and Mathematics Commons^™

Heed The Warning Signs: The Effectiveness Of Message Popup Warnings For Deterring The Spread Of Misinformation, Hollis Greenberg

CCE Theses and Dissertations

As false news can propagate to others rapidly, social media platforms employ multiple methods to combat misinformation. Debunking techniques are warning features embedded into a platform’s interface that alert readers of misinformation. These warnings have two goals: to “debunk” false information and to prevent the further spread of misinformation. Researchers have evaluated the effectiveness of debunking techniques to understand how users increase their awareness of misinformation, and what users do with the information given in warning messages. Message popup warnings are a newer and understudied type of debunking technique.

The overarching research question of this study was: Are message popup …

Student Attitudes And Intentions To Use Continuous Authentication Methods Applied To Mitigate Impersonation Attacks During E-Assessments, Andrea E. Green

CCE Theses and Dissertations

No solution can ultimately eliminate cheating in online courses. However, universities reserve funding for authentication systems to minimize the threat of cheating in online courses. Most higher education institutions use a combination of authentication methods to secure systems against impersonation attacks during online examinations. Authentication technologies ensure that an online course is protected from impersonation attacks. However, it is important that authentication methods secure systems against impersonation attacks with minimal disruption during an examination. Authentication methods applied to secure e-assessments against impersonation attacks may impact a student’s attitude and intentions to use the e-examination system.

In this regard, the research …

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 …

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 …

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 …

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 …

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

CCE Theses and Dissertations

No abstract provided.

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, …

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 …

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’ …

Defining Traffic Scenarios For The Visually Impaired, Judith Jakob, Kordula Kugele, József Tick

The Qualitative Report

For the development of a transfer concept of camera-based object detections from Advanced Driver Assistance Systems to the assistance of the visually impaired, we define relevant traffic scenarios and vision use cases by means of problem-centered interviews with four experts and ten members of the target group. We identify the six traffic scenarios: general orientation, navigating to an address, crossing a road, obstacle avoidance, boarding a bus, and at the train station clustered into the three categories: Orientation, Pedestrian, and Public Transport. Based on the data, we describe each traffic scenario and derive a summarizing table adapted from software engineering …

Examining The Relationship Between Stomiiform Fish Morphology And Their Ecological Traits, Mikayla L. Twiss

All HCAS Student Capstones, Theses, and Dissertations

Trait-based ecology characterizes individuals’ functional attributes to better understand and predict their interactions with other species and their environments. Utilizing morphological traits to describe functional groups has helped group species with similar ecological niches that are not necessarily taxonomically related. Within the deep-pelagic fishes, the Order Stomiiformes exhibits high morphological and species diversity, and many species undertake diel vertical migration (DVM). While the morphology and behavior of stomiiform fishes have been extensively studied and described through taxonomic assessments, the connection between their form and function regarding their DVM types, morphotypes, and daytime depth distributions is not well known. Here, three …

Seizure Prediction In Epilepsy Patients, Gary Dean Cravens

NSU REACH and IPE Day

Purpose/Objective: Characterize rigorously the preictal period in epilepsy patients to improve the development of seizure prediction techniques. Background/Rationale: 30% of epilepsy patients are not well-controlled on medications and would benefit immensely from reliable seizure prediction. Methods/Methodology: Computational model consisting of in-silico Hodgkin-Huxley neurons arranged in a small-world topology using the Watts-Strogatz algorithm is used to generate synthetic electrocorticographic (ECoG) signals. ECoG data from 18 epilepsy patients is used to validate the model. Unsupervised machine learning is used with both patient and synthetic data to identify potential electrophysiologic biomarkers of the preictal period. Results/Findings: The model has shown states corresponding to …

Factors Affecting Customers’ Decision To Share Personal Data With Mobile Operators, Ammar Ali Qaffaf

CCE Theses and Dissertations

Companies that personalize their services based on users’ specific needs have increased sales and customer satisfaction. Personalization requires analyzing the user’s behavior and correlating the action with other pieces of information. The information available for cellular service providers has grown substantially as connectivity becomes ubiquitous. Customers are unknowingly sharing their locations, habits, activities, and preferences in real-time with their service providers. Although cellular service providers state that they share personal data with external entities in their publicly available privacy policies, users have limited control over who can access their personal information. Users have no, or suboptimal, control to manage their …

Diagnosis Of Errors In Stalled Inter-Organizational Workflow Processes, Mudassar Habib Ghazi

CCE Theses and Dissertations

Fault-tolerant inter-organizational workflow processes help participant organizations efficiently complete their business activities and operations without extended delays. The stalling of inter-organizational workflow processes is a common hurdle that causes organizations immense losses and operational difficulties. The complexity of software requirements, incapability of workflow systems to properly handle exceptions, and inadequate process modeling are the leading causes of errors in the workflow processes.

The dissertation effort is essentially about diagnosing errors in stalled inter-organizational workflow processes. The goals and objectives of this dissertation were achieved by designing a fault-tolerant software architecture of workflow system’s components/modules (i.e., workflow process designer, workflow engine, …

Information Systems Security Countermeasures: An Assessment Of Older Workers In Indonesian Small And Medium-Sized Businesses, Hari Samudra Roosman

CCE Theses and Dissertations

Information Systems (IS) misuse can result in cyberattacks such as denial-of-service, phishing, malware, and business email compromise. The study of factors that contribute to the misuse of IS resources is well-documented and empirical research has supported the value of approaches that can be used to deter IS misuse among employees; however, age and cultural nuances exist. Research focusing on older workers and how they can help to deter IS misuse among employees and support cybersecurity countermeasures within developing countries is in its nascent stages. The goal of this study was two-fold. The first goal was to assess what older workers …

Experimental Study To Assess The Role Of Environment And Device Type On The Success Of Social Engineering Attacks: The Case Of Judgment Errors, Tommy Pollock

CCE Theses and Dissertations

Phishing continues to be an invasive threat to computer and mobile device users. Cybercriminals continuously develop new phishing schemes using e-mail and malicious search engine links to gather the personal information of unsuspecting users. This information is used for financial gains through identity theft schemes or draining victims' financial accounts. Many users of varying demographic backgrounds fall victim to phishing schemes at one time or another. Users are often distracted and fail to process the phishing attempts fully, then unknowingly fall victim to the scam until much later. Users operating mobile phones and computers are likely to make judgment errors …

A Validity-Based Approach For Feature Selection In Intrusion Detection Systems, Eljilani Hmouda

CCE Theses and Dissertations

Intrusion detection systems are tools that detect and remedy the presence of malicious activities. Intrusion detection systems face many challenges in terms of accurate analysis and evaluation. One such challenge is the involvement of many features during analysis, which leads to high data volume and ultimately excessive computational overhead. This research surrounds the development of a new intrusion detection system by employing an entropy-based measure called v-measure to select significant features and reduce dimensionality. After the development of the intrusion detection system, this feature reduction technique was tested on public datasets by applying machine learning classifiers such as Decision Tree, …

Impact Of Knowledge Management Processes Upon Job Satisfaction And Job Performance, George Reid Cooper

CCE Theses and Dissertations

While we might know anecdotally that the implementation of knowledge management in an organization improves job satisfaction and job performance, there are limited empirical studies that assess this assumption. There have been studies done in this area but the results vary in terms of which knowledge management processes have an impact upon job satisfaction and which do not. Similarly, many studies make assumptions that job satisfaction leads to improved job performance without testing for that variable. The goal of this dissertation is to assess whether the knowledge management processes have a positive impact upon job satisfaction and job performance and …

Exploring The Existing And Unknown Side Effects Of Privacy Preserving Data Mining Algorithms, Hima Bindu Sadashiva Reddy

CCE Theses and Dissertations

The data mining sanitization process involves converting the data by masking the sensitive data and then releasing it to public domain. During the sanitization process, side effects such as hiding failure, missing cost and artificial cost of the data were observed. Privacy Preserving Data Mining (PPDM) algorithms were developed for the sanitization process to overcome information loss and yet maintain data integrity. While these PPDM algorithms did provide benefits for privacy preservation, they also made sure to solve the side effects that occurred during the sanitization process. Many PPDM algorithms were developed to reduce these side effects. There are several …

Social Media Analytics And Information Privacy Decisions: Impact Of User Intimate Knowledge And Co-Ownership Perceptions, Bradley Alukwe Wangia

CCE Theses and Dissertations

Social media analytics has been recognized as a distinct research field in the analytics subdomain that is developed by processing social media content to generate important business knowledge. Understanding the factors that influence privacy decisions around its use is important as it is often perceived to be opaque and mismanaged. Social media users have been reported to have low intimate knowledge and co-ownership perception of social media analytics and its information privacy decisions. This deficiency leads them to perceive privacy violations if firms make privacy decisions that conflict with their expectations. Such perceived privacy violations often lead to business disruptions …

An Empirical Investigation Of The Evidence Recovery Process In Digital Forensics, Kevin Parviz

CCE Theses and Dissertations

The widespread use of the digital media in committing crimes, and the steady increase of their storage capacity has created backlogs at digital forensic labs. The problem is exacerbated especially in high profile crimes. In many such cases the judicial proceedings mandate full analysis of the digital media, when doing so is rarely accomplished or practical. Prior studies have proposed different phases for forensic analysis, to lessen the backlog issues. However, these phases are not distinctly differentiated, and some proposed solutions may not be practical. This study utilized several past police forensic analyses. Each case was chosen for having five …

A Universal Cybersecurity Competency Framework For Organizational Users, Patricia A. Baker

CCE Theses and Dissertations

The global reliance on the Internet to facilitate organizational operations necessitates further investments in organizational information security. Such investments hold the potential for protecting information assets from cybercriminals. To assist organizations with their information security, The National Initiative for Cybersecurity Education (NICE) Cybersecurity Workforce Framework (NCWF) was created. The framework referenced the cybersecurity work, knowledge, and skills required to competently complete the tasks that strengthen their information security. Organizational users’ limited cybersecurity competency contributes to the financial and information losses suffered by organizations year after year. While most organizational users may be able to respond positively to a cybersecurity threat, …

Modified Structured Domain Randomization In A Synthetic Environment For Learning Algorithms, Bryan L. Croft

CCE Theses and Dissertations

Deep Reinforcement Learning (DRL) has the capability to solve many complex tasks in robotics, self-driving cars, smart grids, finance, healthcare, and intelligent autonomous systems. During training, DRL agents interact freely with the environment to arrive at an inference model. Under real-world conditions this training creates difficulties of safety, cost, and time considerations. Training in synthetic environments helps overcome these difficulties, however, this only approximates real-world conditions resulting in a ‘reality gap’. The synthetic training of agents has proven advantageous but requires methods to bridge this reality gap. This work addressed this through a methodology which supports agent learning. A framework …

An Approach For Efficient Robust Adversarial Training In Deep Neural Networks, Cesar Zalzalah

CCE Theses and Dissertations

With advancements in computer hardware, deep neural networks outperform other methods for many applications, such as image and voice recognition. Unfortunately, existing deep neural networks are fragile at test time against adversarial examples, which are intentionally calculated perturbations that cause a neural network to misclassify the correct input label. This vulnerability makes the use of neural networks risky, especially in critical applications. Extensive prior research studies to build a robust neural network using diverse approaches have been proposed to tackle this problem, including customized models and their parameters, input pre-processing to detect and remove adversarial perturbations, blocking the adversarial input, …

An Assessment Of The Impacts Of Social Media Inputs And Court Case Information On Mitigating Insider Threats, Robert Jones

CCE Theses and Dissertations

The insider threat is a global problem that impacts organizations and produces a gamut of undesired outcomes. Businesses often experience lost revenue and stolen trade secrets, which can leave a tarnished reputation. Insider threats can also cause harm to individuals and national security. Past efforts have not mitigated the problem in its entirety. Documented instances of insider threats are as recent as March 2020. Many researchers have focused on monitoring technologies and relying on human monitoring in a reactive posture. An ideal solution would scrutinize an individual’s character and ascertain whether unique traits associated with actors of insider threats are …

The Influence Of An Individual’S Disposition To Value Privacy In A Non-Contrived Study, John Marsh

CCE Theses and Dissertations

Unexpected usage of user data has made headlines as both governments and commercial entities have encountered privacy-related issues. Like other social networking sites, LinkedIn provides users to restrict access to their information or allow for public viewing; information available in the public view was used unexpectedly (i.e., profiling). A non-profit entity called ICWATCH used tools to gather information on government mass surveillance programs by scraping publicly accessible user data from LinkedIn. Previous research has shown that privacy concerns influence behavior intention in contrived scenarios. What remains unclear is whether LinkedIn users, whose data was scraped by ICWATCH (an actual situation), …

Examining The Influence Of Perceived Risk On The Selection Of Internet Access In The U.S. Intelligence Community, Tyler Michael Pieron

CCE Theses and Dissertations

Information technology security policies are designed explicitly to protect IT systems. However, overly restrictive information security policies may be inadvertently creating an unforeseen information risk by encouraging users to bypass protected systems in favor of personal devices, where the potential loss of organizational intellectual property is greater.

Current models regarding the acceptance and use of technology, Technology Acceptance Model Version 3 (TAM3) and the Unified Theory of Acceptance and Use of Technology Version 2 (UTAUT2), address the use of technology in organizations and by consumers, but little research has been done to identify an appropriate model to begin to understand …

Feature Selection On Permissions, Intents And Apis For Android Malware Detection, Fred Guyton

CCE Theses and Dissertations

Malicious applications pose an enormous security threat to mobile computing devices. Currently 85% of all smartphones run Android, Google’s open-source operating system, making that platform the primary threat vector for malware attacks. Android is a platform that hosts roughly 99% of known malware to date, and is the focus of most research efforts in mobile malware detection due to its open source nature. One of the main tools used in this effort is supervised machine learning. While a decade of work has made a lot of progress in detection accuracy, there is an obstacle that each stream of research is …

Orientation And Social Influences Matter: Revisiting Neutralization Tendencies In Information Systems Security Violation, Frank Curtis King

CCE Theses and Dissertations

It is estimated that over half of all information systems security breaches are due directly or indirectly to the poor security practices of an organization’s employees. Previous research has shown neutralization techniques as having influence on the intent to violate information security policy. In this study, we proposed an expansion of the neutralization model by including the effects of business and ethical orientation of individuals on their tendencies to neutralize and compromise with information security policy. Additionally, constructs from social influences and pressures have been integrated into this model to measure the impact on the intent to violate information security …