Computer Sciences Commons^™

Standardizing Instructional Definition And Content Supporting Information Security Compliance Requirements, Theresa Curran

CCE Theses and Dissertations

Information security (IS)-related risks affect global public and private organizations on a daily basis. These risks may be introduced through technical or human-based activities, and can include fraud, hacking, malware, insider abuse, physical loss, mobile device misconfiguration or unintended disclosure. Numerous and diverse regulatory and contractual compliance requirements have been mandated to assist organizations proactively prevent these types of risks. Two constants are noted in these requirements. The first constant is requiring organizations to disseminate security policies addressing risk management through secure behavior. The second constant is communicating policies through IS awareness, training and education (ISATE) programs. Compliance requirements direct …

A Developmental Research Of A Taxonomy For Employees’ Mobile Device Cyberslacking And Commitment To The Organization In The Context Of Productivity, Saleh Alharthi

CCE Theses and Dissertations

While the introduction of the Internet facilitated the communication channels at the workplace to improve employees’ productivity, it also raised new challenges, such as Internet use for personal activities. Organizations face productivity losses due to employees’ involvement in counterproductive behaviors, such as cyberslacking. The frequency of mobile device cyberslacking is anticipated to increase due to continuous developments in online connectivity, applications, and the significant growth of mobile device usage worldwide. In addition, research has shown that employees’ commitment to their organization can encourage behaviors that positively influence productivity. Employee’s commitment is a crucial factor because it can benefit an organization …

Development, Implementation, And Assessment Of An Online Doctoral Student Orientation, Russell J. Garner

CCE Theses and Dissertations

An examination of the recent literature revealed there are no established standards for orienting online doctoral students. To address this problem, the relevant literature was examined and suggested that doctoral students can be effectively oriented to their academic environment when provided with the requisite programmatic and institutional information, and factors that support socialization and self-efficacy.

A literature-based orientation was developed to examine its impact on students’ first semester success in terms of rates of retention and grade point averages (GPA). This was accomplished using a developmental study approach that included three primary phases: 1) development of a literature-based orientation; 2) …

Wireless Sensor Network Clustering With Machine Learning, Larry Townsend

CCE Theses and Dissertations

Wireless sensor networks (WSNs) are useful in situations where a low-cost network needs to be set up quickly and no fixed network infrastructure exists. Typical applications are for military exercises and emergency rescue operations. Due to the nature of a wireless network, there is no fixed routing or intrusion detection and these tasks must be done by the individual network nodes. The nodes of a WSN are mobile devices and rely on battery power to function. Due the limited power resources available to the devices and the tasks each node must perform, methods to decrease the overall power consumption of …

Comparing Training Methodologies On Employee’S Cybersecurity Countermeasures Awareness And Skills In Traditional Vs. Socio-Technical Programs, Jodi Goode

CCE Theses and Dissertations

Organizations, which have established an effective technical layer of security, continue to experience difficulties triggered by cyber threats. Ultimately, the cybersecurity posture of an organization depends on appropriate actions taken by employees whose naive cybersecurity practices have been found to represent 72% to 95% of cybersecurity threats and vulnerabilities to organizations. However, employees cannot be held responsible for cybersecurity practices if they are not provided the education and training to acquire skills, which allow for identification of security threats along with the proper course of action to mitigate such threats. In addition, awareness of the importance of cybersecurity, the responsibility …

Probabilistic Clustering Ensemble Evaluation For Intrusion Detection, Steven M. Mcelwee

CCE Theses and Dissertations

Intrusion detection is the practice of examining information from computers and networks to identify cyberattacks. It is an important topic in practice, since the frequency and consequences of cyberattacks continues to increase and affect organizations. It is important for research, since many problems exist for intrusion detection systems. Intrusion detection systems monitor large volumes of data and frequently generate false positives. This results in additional effort for security analysts to review and interpret alerts. After long hours spent reviewing alerts, security analysts become fatigued and make bad decisions. There is currently no approach to intrusion detection that reduces the workload …

An Empirical Assessment Of Senior Citizens’ Cybersecurity Awareness, Computer Self-Efficacy, Perceived Risk Of Identity Theft, Attitude, And Motivation To Acquire Cybersecurity Skills, Carlene G. Blackwood-Brown

CCE Theses and Dissertations

Cyber-attacks on Internet users have caused billions of dollars in losses annually. Cybercriminals launch attacks via threat vectors such as unsecured wireless networks and phishing attacks on Internet users who are usually not aware of such attacks. Senior citizens are one of the most vulnerable groups who are prone to cyber-attacks, and this is largely due to their limited cybersecurity awareness and skills. Within the last decade, there has been a significant increase in Internet usage among senior citizens. It was documented that senior citizens had the greatest rate of increase in Internet usage over all the other age groups …

Machine Learning Methods For Septic Shock Prediction, Aiman A. Darwiche

CCE Theses and Dissertations

Sepsis is an organ dysfunction life-threatening disease that is caused by a dysregulated body response to infection. Sepsis is difficult to detect at an early stage, and when not detected early, is difficult to treat and results in high mortality rates. Developing improved methods for identifying patients in high risk of suffering septic shock has been the focus of much research in recent years. Building on this body of literature, this dissertation develops an improved method for septic shock prediction. Using the data from the MMIC-III database, an ensemble classifier is trained to identify high-risk patients. A robust prediction model …

Novel Alert Visualization: The Development Of A Visual Analytics Prototype For Mitigation Of Malicious Insider Cyber Threats, Karla A. Clarke

CCE Theses and Dissertations

Cyber insider threat is one of the most difficult risks to mitigate in organizations. However, innovative validated visualizations for cyber analysts to better decipher and react to detected anomalies has not been reported in literature or in industry. Attacks caused by malicious insiders can cause millions of dollars in losses to an organization. Though there have been advances in Intrusion Detection Systems (IDSs) over the last three decades, traditional IDSs do not specialize in anomaly identification caused by insiders. There is also a profuse amount of data being presented to cyber analysts when deciphering big data and reacting to data …

Machine Learning For Exploring State Space Structure In Genetic Regulatory Networks, Rodney H. Thomas

CCE Theses and Dissertations

Genetic regulatory networks (GRN) offer a useful model for clinical biology. Specifically, such networks capture interactions among genes, proteins, and other metabolic factors. Unfortunately, it is difficult to understand and predict the behavior of networks that are of realistic size and complexity. In this dissertation, behavior refers to the trajectory of a state, through a series of state transitions over time, to an attractor in the network. This project assumes asynchronous Boolean networks, implying that a state may transition to more than one attractor. The goal of this project is to efficiently identify a network's set of attractors and to …

Assessment Of Factors Influencing Intent-To-Use Big Data Analytics In An Organization: A Survey Study, Wayne Madhlangobe

CCE Theses and Dissertations

The central question was how the relationship between trust-in-technology and intent-to-use Big Data Analytics in an organization is mediated by both Perceived Risk and Perceived Usefulness. Big Data Analytics is quickly becoming a critically important driver for business success. Many organizations are increasing their Information Technology budgets on Big Data Analytics capabilities. Technology Acceptance Model stands out as a critical theoretical lens primarily due to its assessment approach and predictive explanatory capacity to explain individual behaviors in the adoption of technology. Big Data Analytics use in this study was considered a voluntary act, therefore, well aligned with the Theory of …

Knowledge Sharing Among Academics In Higher Education Institutions In Saudi Arabia, Fahad M. Alsaadi

CCE Theses and Dissertations

The Ministry of Higher Education (MOHE) in Saudi Arabia aims to move toward a knowledge-based economy and many knowledge management (KM) and knowledge sharing (KS) initiatives have been taken to accelerate the achievement of this goal. Despite the substantial body of research into KS in the business environment, research that investigates factors that promote KS practices among academics in higher education institutions (HEIs) is generally limited, but particularly in Saudi Arabia. To bridge this gap, the goal was to explore what individual and organizational factors contribute to a person’s willingness to share knowledge and develop a profile of the current …

Computer-Supported Collaborative Learning Using Augmented And Virtual Reality In Museum Education, Ronald Punako Jr.

CCE Theses and Dissertations

Recent advancements in the cost, availability, and capability of augmented reality (AR) and virtual reality (VR) devices and software are spurring their mass distribution to the public. This fundamental shift in the use of AR and VR predominantly from military and academic research laboratories to the public presents new opportunities and challenges for the design of instructional technology. While studies of AR and VR have been conducted to inform the design of individual instructional products, few studies have focused on computer-supported collaborative learning (CSCL) products in which AR and VR learners work together toward shared learning goals.

The museum education …

Perceptions Of Female Cybersecurity Professionals Toward Factors That Encourage Females To The Cybersecurity Field, Kembley Kay Lingelbach

CCE Theses and Dissertations

Despite multiple national, educational, and industry initiatives, women continue to be underrepresented in the cybersecurity field. Only 11% of cybersecurity professionals, globally, are female. This contributes to the growing overall shortage of workers in the field. This research addressed the significant underrepresentation of females in the cybersecurity workforce. There are many practitioner and industry studies that suggest self-efficacy, discrimination and organizational culture play important roles in the low rate of women in the cybersecurity field. A limited number of scholarly studies identify causal factors; however, there is not a general consensus or framework to explain the problem thoroughly. Moreover, there …

Multi-Robot Complete Coverage Using Directional Constraints, Stefanus Malan

CCE Theses and Dissertations

Complete coverage relies on a path planning algorithm that will move one or more robots, including the actuator, sensor, or body of the robot, over the entire environment. Complete coverage of an unknown environment is used in applications like automated vacuum cleaning, carpet cleaning, lawn mowing, chemical or radioactive spill detection and cleanup, and humanitarian de-mining.

The environment is typically decomposed into smaller areas and then assigned to individual robots to cover. The robots typically use the Boustrophedon motion to cover the cells. The location and size of obstacles in the environment are unknown beforehand. An online algorithm using sensor-based …

The Impact Of Cost On Feature Selection For Classifiers, Richard Clyde Mccrae

CCE Theses and Dissertations

Supervised machine learning models are increasingly being used for medical diagnosis. The diagnostic problem is formulated as a binary classification task in which trained classifiers make predictions based on a set of input features. In diagnosis, these features are typically procedures or tests with associated costs. The cost of applying a trained classifier for diagnosis may be estimated as the total cost of obtaining values for the features that serve as inputs for the classifier. Obtaining classifiers based on a low cost set of input features with acceptable classification accuracy is of interest to practitioners and researchers. What makes this …

The Influence Of Website Design On Online Trust In Electronic Commerce Retailing Environments, Dinesh Khialani

CCE Theses and Dissertations

E-commerce retail sales continue to experience significant growth in the United States (U.S.) annually. However, the contribution of e-commerce retail sales towards total retail sales in the U.S. remains low. Furthermore, the growth of e-commerce retail sales from year to year as a percentage of total retail sales in the U.S. is also fractional. The lack of online trust by consumers has been cited as a significant barrier to transacting online and a possible cause of this slow-moving trend.

E-commerce retail sales are paramount to the success and profitability of online merchants. It remains critical to understand the underlying determinants …

Evaluation Of Machine Learning Techniques For Early Identification Of At-Risk Students, Mansour Hamoud Awaji

CCE Theses and Dissertations

Student attrition is one of the long-standing problems facing higher education institutions despite the extensive research that has been undertaken to address it. To increase students’ success and retention rates, there is a need for early alert systems that facilitate the identification of at-risk students so that remedial measures may be taken in time to reduce the risk. However, incorporating ML predictive models into early warning systems face two main challenges: improving the accuracy of timely predictions and the generalizability of predictive models across on-campus and online courses. The goal of this study was to develop and evaluate predictive models …

Development And Validation Of A Proof-Of-Concept Prototype For Analytics-Based Malicious Cybersecurity Insider Threat In A Real-Time Identification System, Angel L. Hueca

CCE Theses and Dissertations

Insider threat has continued to be one of the most difficult cybersecurity threat vectors detectable by contemporary technologies. Most organizations apply standard technology-based practices to detect unusual network activity. While there have been significant advances in intrusion detection systems (IDS) as well as security incident and event management solutions (SIEM), these technologies fail to take into consideration the human aspects of personality and emotion in computer use and network activity, since insider threats are human-initiated. External influencers impact how an end-user interacts with both colleagues and organizational resources. Taking into consideration external influencers, such as personality, changes in organizational polices …

Development Of A Client-Side Evil Twin Attack Detection System For Public Wi-Fi Hotspots Based On Design Science Approach, Liliana R. Horne

CCE Theses and Dissertations

Users and providers benefit considerably from public Wi-Fi hotspots. Users receive wireless Internet access and providers draw new prospective customers. While users are able to enjoy the ease of Wi-Fi Internet hotspot networks in public more conveniently, they are more susceptible to a particular type of fraud and identify theft, referred to as evil twin attack (ETA). Through setting up an ETA, an attacker can intercept sensitive data such as passwords or credit card information by snooping into the communication links. Since the objective of free open (unencrypted) public Wi-Fi hotspots is to provide ease of accessibility and to entice …