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Computer Sciences Commons

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Nova Southeastern University

Theses/Dissertations

2022

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Full-Text Articles in Computer Sciences

Examining The Relationship Between Stomiiform Fish Morphology And Their Ecological Traits, Mikayla L. Twiss Dec 2022

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 …


Diagnosis Of Errors In Stalled Inter-Organizational Workflow Processes, Mudassar Habib Ghazi Jan 2022

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, …


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 Jan 2022

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 Universal Cybersecurity Competency Framework For Organizational Users, Patricia A. Baker Jan 2022

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, …


Information Systems Security Countermeasures: An Assessment Of Older Workers In Indonesian Small And Medium-Sized Businesses, Hari Samudra Roosman Jan 2022

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 …


An Empirical Investigation Of The Evidence Recovery Process In Digital Forensics, Kevin Parviz Jan 2022

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 …


Exploring The Existing And Unknown Side Effects Of Privacy Preserving Data Mining Algorithms, Hima Bindu Sadashiva Reddy Jan 2022

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 …


Factors Affecting Customers’ Decision To Share Personal Data With Mobile Operators, Ammar Ali Qaffaf Jan 2022

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 …


Social Media Analytics And Information Privacy Decisions: Impact Of User Intimate Knowledge And Co-Ownership Perceptions, Bradley Alukwe Wangia Jan 2022

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 …


Modified Structured Domain Randomization In A Synthetic Environment For Learning Algorithms, Bryan L. Croft Jan 2022

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 …


A Validity-Based Approach For Feature Selection In Intrusion Detection Systems, Eljilani Hmouda Jan 2022

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 Jan 2022

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 …


An Approach For Efficient Robust Adversarial Training In Deep Neural Networks, Cesar Zalzalah Jan 2022

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, …