Computer Sciences Commons^™

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

CCAC 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 …

Adversarial Training Of Deep Neural Networks, Anabetsy Termini

CCAC 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

CCAC 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’ …

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

CCAC 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 …

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

CCAC 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, …

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 …

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

CCAC 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, …

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

CCAC 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 …

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

CCAC 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 …

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

CCAC 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

CCAC 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 …

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

CCAC 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

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

CCAC 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

CCAC 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 …

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

CCAC 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, …

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

CCAC 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, …

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

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

CCAC 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 …

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

CCAC 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 …

Investigation Of Ant Colony Optimization Implementation Strategies For Low-Memory Operating Environments, Douglas Hale

CCAC Theses and Dissertations

In search guided by meta-heuristics, a fundamental tradeoff exists between exploitation of good solutions (intensification) and exploration of the solution space for better solutions (diversification). Over-exploitation can limit the search to suboptimal solutions while over-exploration can reduce the efficiency of the overall search. Ant Colony Optimization (ACO) is a well-known meta-heuristic inspired by biological ants for solving NP-hard combinatorial search problems like the Traveling Salesman Problem (TSP). In nature, biological ant colonies navigate to find efficient paths around complex obstacles by depositing and following simple chemicals called pheromones. ACO algorithms model this behavior by implementing sets of artificial ants which …

A Framework For Artificial Intelligence Applications In The Healthcare Revenue Management Cycle, Leonard J. Pounds

CCAC Theses and Dissertations

There is a lack of understanding of specific risks and benefits associated with AI/RPA implementations in healthcare revenue cycle settings. Healthcare companies are confronted with stricter regulations and billing requirements, underpayments, and more significant delays in receiving payments. Despite the continued interest of practitioners, revenue cycle management has not received much attention in research. Revenue cycle management is defined as the process of identifying, collecting, and managing the practice’s revenue from payers based on the services provided.This dissertation provided contributions to both areas, as mentioned above. To accomplish this, a semi-structured interview was distributed to healthcare executives. The semi-structured interview …

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

CCAC 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

CCAC 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 …

Examination Of Corporate Investments In Privacy: An Event Study, Joseph Michael Squillace

CCAC Theses and Dissertations

The primary objective of any corporate entity is generating as much wealth as possible. Investing financially in technology domains has historically been a successful strategy for generating increased corporate and shareholder wealth. However, investments in Information Technology (IT), Information Systems (IS) and Information Security (InfoSec) to specifically generate increased wealth must be implemented carefully.

Shareholders reacting to corporate investments perceive financial value from individual investments. The investment’s perceived value is then reflected in the corporation’s updated stock market value. IS, IT, and InfoSec investments perceived to possess positive financial value, indicating strong potential for increased wealth, are rewarded by shareholders …

Pause For A Cybersecurity Cause: Assessing The Influence Of A Waiting Period On User Habituation In Mitigation Of Phishing Attacks, Amy Antonucci

CCAC Theses and Dissertations

Social engineering costs organizations billions of dollars a year. Social engineering exploits the weakest link of information security systems, the people who are using them. Phishing is a form of social engineering in which the perpetrator depends on the victim’s instinctual thinking towards an email designed to create a fear or excitement response. It is well-documented in literature that users continue to click on phishing emails costing them and their employers significant monetary resources and data loss. Training does not appear to mitigate the effects of phishing much; other solutions are necessary to mitigate phishing.

Kahneman introduced the concepts of …

Increasing Software Reliability Using Mutation Testing And Machine Learning, Michael Allen Stewart

CCAC Theses and Dissertations

Mutation testing is a type of software testing proposed in the 1970s where program statements are deliberately changed to introduce simple errors so that test cases can be validated to determine if they can detect the errors. The goal of mutation testing was to reduce complex program errors by preventing the related simple errors. Test cases are executed against the mutant code to determine if one fails, detects the error and ensures the program is correct. One major issue with this type of testing was it became intensive computationally to generate and test all possible mutations for complex programs.

This …

An Empirical Assessment Of Users' Information Security Protection Behavior Towards Social Engineering Breaches, Nisha Jatin Patel

CCAC Theses and Dissertations

User behavior is one of the most significant information security risks. Information Security is all about being aware of who and what to trust and behaving accordingly. Due to technology becoming an integral part of nearly everything in people's daily lives, the organization's need for protection from security threats has continuously increased. Social engineering is the act of tricking a user into revealing information or taking action. One of the riskiest aspects of social engineering is that it depends mainly upon user errors and is not necessarily a technology shortcoming. User behavior should be one of the first apprehensions when …