Computer Sciences Commons^™

Sns As An Educational Tool: Effect On Academic Performance And Learners’ Perceptions, Nawwaf Mohssen Altalhi

CCAC Theses and Dissertations

With Social Networking Sites (SNSs) being extensively used by students, there has been extensive research in relation to their ability to enhance students’ academic performance in various learning environments, although the advent of research on online learning is a recent development.

Studies regarding the use of SNSs indicated that there was a negative relationship between students’ use of SNSs and students’ academic performance. However, it is unknown whether the implementation of an instructional training course utilizing SNSs as an educational tool might lead to improvements in students’ academic performance. Many students have admitted to not knowing how to properly use …

A Hierarchical Temporal Memory Sequence Classifier For Streaming Data, Jeffrey Barnett

CCAC Theses and Dissertations

Real-world data streams often contain concept drift and noise. Additionally, it is often the case that due to their very nature, these real-world data streams also include temporal dependencies between data. Classifying data streams with one or more of these characteristics is exceptionally challenging. Classification of data within data streams is currently the primary focus of research efforts in many fields (i.e., intrusion detection, data mining, machine learning). Hierarchical Temporal Memory (HTM) is a type of sequence memory that exhibits some of the predictive and anomaly detection properties of the neocortex. HTM algorithms conduct training through exposure to a stream …

An Approach To Twitter Event Detection Using The Newsworthiness Metric, Jonathan Adkins

CCAC Theses and Dissertations

No abstract provided.

Detecting Rogue Manipulation Of Smart Home Device Settings, David Zeichick

CCAC Theses and Dissertations

Smart home devices control a home’s environmental and security settings. This includes devices that control home thermostats, sprinkler systems, light bulbs, and home appliances. Malicious manipulation of the settings of these devices by an outside adversary has caused emotional distress and could even cause physical harm. For example, researchers have reported that there is a rise in domestic abuse perpetrated via smart home devices; victims have reported their thermostat settings being unwittingly manipulated and being locked out of their house due to their smart lock code being changed. Rapid adoption of smart home devices by consumers has led to an …

Development Of Criteria For Mobile Device Cybersecurity Threat Classification And Communication Standards (Ctc&Cs), Emmanuel Jigo

CCAC Theses and Dissertations

The increasing use of mobile devices and the unfettered access to cyberspace has introduced new threats to users. Mobile device users are continually being targeted for cybersecurity threats via vectors such as public information sharing on social media, user surveillance (geolocation, camera, etc.), phishing, malware, spyware, trojans, and keyloggers. Users are often uninformed about the cybersecurity threats posed by mobile devices. Users are held responsible for the security of their device that includes taking precautions against cybersecurity threats. In recent years, financial institutions are passing the costs associated with fraud to the users because of the lack of security.

The …

Unix Administrator Information Security Policy Compliance: The Influence Of A Focused Seta Workshop And Interactive Security Challenges On Heuristics And Biases, John Palmer Mcconnell

CCAC Theses and Dissertations

Information Security Policy (ISP) compliance is crucial to the success of healthcare organizations due to security threats and the potential for security breaches. UNIX Administrators (UXAs) in healthcare Information Technology (IT) maintain critical servers that house Protected Health Information (PHI). Their compliance with ISP is crucial to the confidentiality, integrity, and availability of PHI data housed or accessed by their servers. The use of cognitive heuristics and biases may negatively influence threat appraisal, coping appraisal, and ultimately ISP compliance behavior. These failures may result in insufficiently protected servers and put organizations at greater risk of data breaches and financial loss. …

Cybersecurity Risk-Responsibility Taxonomy: The Role Of Cybersecurity Social Responsibility In Small Enterprises On Risk Of Data Breach, Keiona Davis

CCAC Theses and Dissertations

With much effort being placed on the physical, procedural, and technological solutions for Information Systems (IS) cybersecurity, research studies tend to focus their efforts on large organizations while overlooking very smaller organizations (below 50 employees). This study addressed the failure to prevent data breaches in Very Small Enterprises (VSEs). VSEs contribute significantly to the economy, however, are more prone to cyber-attacks due to the limited risk mitigations on their systems and low cybersecurity skills of their employees. VSEs utilize Point-of-Sale (POS) systems that are exposed to cyberspace, however, they are often not equipped to prevent complex cybersecurity issues that can …

The Social Media Machines: An Investigation Of The Effect Of Trust Moderated By Disinformation On Users’ Decision-Making Process, Zulma Valedon Westney

CCAC Theses and Dissertations

Social media networking sites (SMNS) have become a popular communications medium where users share information, knowledge, and persuasion. In less than two decades, social media's (SM) dominance as a communication medium can't be disputed, for good or evil. Combined with the newly found immediacy and pervasiveness, these SM applications' persuasive power are useful weapons for organizations, angry customers, employees, actors, and activists bent on attacking or hacking other individuals, institutions, or systems. Consequently, SM has become the preferred default mechanism of news sources; however, users are unsure if the information gathered is true or false. According to the literature, SMNS …

Protecting The Protector: Mapping The Key Terrain That Supports The Continuous Monitoring Mission Of A Cloud Cybersecurity Service Provider, Chris Bush

CCAC Theses and Dissertations

Key terrain is a concept that is relevant to warfare, military strategy, and tactics. A good general maps out terrain to identify key areas to protect in support of a mission (i.e., a bridge allowing for mobility of supplies and reinforcements). Effective ways to map terrain in Cyberspace (KT-C) has been an area of interest for researchers in Cybersecurity ever since the Department of Defense designated Cyberspace as a warfighting domain. The mapping of KT-C for a mission is accomplished by putting forth efforts to understand and document a mission's dependence on Cyberspace and cyber assets. A cloud Cybersecurity Service …

A Novel S-Box-Based Postprocessing Method For True Random Number Generation, Erdi̇nç Avaroğlu, Taner Tuncer

Turkish Journal of Electrical Engineering and Computer Sciences

The quality of randomness in numbers generated by true random number generators (TRNGs) depends on the source of entropy. However, in TRNGs, sources of entropy are affected by environmental changes and this creates a correlation between the generated bit sequences. Postprocessing is required to remove the problem created by this correlation in TRNGs. In this study, an S-box-based postprocessing structure is proposed as an alternative to the postprocessing structures seen in the published literature. A ring oscillator (RO)-based TRNG is used to demonstrate the use of an S-box for postprocessing and the removal of correlations between number sequences. The statistical …

Harmonic Effects Optimization At A System Level Using A Harmonic Power Flowcontroller, Reza Mehri, Hossein Mokhtari

Turkish Journal of Electrical Engineering and Computer Sciences

Increase of nonlinear loads in industries has resulted in high levels of harmonic currents and consequently harmonic voltages in power networks. Harmonics have several negative effects such as higher energy losses and equipment life reduction. To reduce the levels of harmonics in power networks, different methods of harmonic suppression have been employed. The basic idea in all of these methods is to prevent harmonics from flowing into a power network at customer sides and the point of common coupling (PCC). Due to the costs, none of the existing mitigating methods result in a harmonic-free power system. The remaining harmonic currents, …

The Ai Author In Litigation, Yvette Joy Liebesman, Julie Cromer Young

All Faculty Scholarship

Many scholars have posited whether a computer possessing Artificial Intelligence (AI) could be considered an author as defined per the Copyright Act of 1976. What was once a thought experiment is now becoming reality. To date, scholarship has focused primarily been on whether an AI meets the requirements of authorship from a purely objective legal framework or whether an AI could be an author based on the doctrines of incentives, independent creation, and creativity.

However, a burden inherent in the rights and liabilities of authorship is the ability to be held liable if that author’s expressive work is infringing on …

Heterogeneous Multi-Layered Network Model For Omics Data Integration And Analysis, Bohyun Lee, Shuo Zhang, Aleksandar Poleksic, Lei Xie

Faculty Work

Advances in next-generation sequencing and high-throughput techniques have enabled the generation of vast amounts of diverse omics data. These big data provide an unprecedented opportunity in biology, but impose great challenges in data integration, data mining, and knowledge discovery due to the complexity, heterogeneity, dynamics, uncertainty, and high-dimensionality inherited in the omics data. Network has been widely used to represent relations between entities in biological system, such as protein-protein interaction, gene regulation, and brain connectivity (i.e. network construction) as well as to infer novel relations given a reconstructed network (aka link prediction). Particularly, heterogeneous multi-layered network (HMLN) has proven successful …

Prediction Of Sudden Cardiac Death Using Ensemble Classifiers, Ayman Momtaz El-Geneidy

CCAC Theses and Dissertations

Sudden Cardiac Death (SCD) is a medical problem that is responsible for over 300,000 deaths per year in the United States and millions worldwide. SCD is defined as death occurring from within one hour of the onset of acute symptoms, an unwitnessed death in the absence of pre-existing progressive circulatory failures or other causes of deaths, or death during attempted resuscitation. Sudden death due to cardiac reasons is a leading cause of death among Congestive Heart Failure (CHF) patients. The use of Electronic Medical Records (EMR) systems has made a wealth of medical data available for research and analysis. Supervised …

Adaptive Batch Size Selection In Active Learning For Regression, Anthony L. Faulds

CCAC Theses and Dissertations

Training supervised machine learning models requires labeled examples. A judicious choice of examples is helpful when there is a significant cost associated with assigning labels. This dissertation aims to improve upon a promising extant method - Batch-mode Expected Model Change Maximization (B-EMCM) method - for selecting examples to be labeled for regression problems. Specifically, it aims to develop and evaluate alternate strategies for adaptively selecting batch size in B-EMCM, named adaptive B-EMCM (AB-EMCM).

By determining the cumulative error that occurs from the estimation of the stochastic gradient descent, a stop criteria for each iteration of the batch can be specified …

The Influence Of Cognitive Factors And Personality Traits On Mobile Device User's Information Security Behavior, Nils Lau

CCAC Theses and Dissertations

As individuals have become more dependent on mobile devices to communicate, to seek information, and to conduct business, their susceptibility to various threats to information security has also increased. Research has consistently shown that a user’s intention is a significant antecedent of information security behavior. Although research on user’s intention has expanded in the last few years, not enough is known about how cognitive factors and personality traits impact the adoption and use of mobile device security technologies.

The purpose of this research was to empirically investigate the influence of cognitive factors and personality traits on mobile device user’s intention …

You Might Be A Robot, Bryan Casey, Mark A. Lemley

Cornell Law Review

As robots and artificial intelligence (Al) increase their influence over society, policymakers are increasingly regulating them. But to regulate these technologies, we first need to know what they are. And here we come to a problem. No one has been able to offer a decent definition of robots arid AI-not even experts. What's more, technological advances make it harder and harder each day to tell people from robots and robots from "dumb" machines. We have already seen disastrous legal definitions written with one target in mind inadvertently affecting others. In fact, if you are reading this you are (probably) not …

A Pcnn Framework For Blood Cell Image Segmentation, Carol D. Lenihan

CCAC Theses and Dissertations

This research presents novel methods for segmenting digital blood cell images under a Pulse Coupled Neural Network (PCNN) framework. A blood cell image contains different types of blood cells found in the peripheral blood stream such as red blood cells (RBCs), white blood cells (WBCs), and platelets. WBCs can be classified into five normal types – neutrophil, monocyte, lymphocyte, eosinophil, and basophil – as well as abnormal types such as lymphoblasts and others. The focus of this research is on identifying and counting RBCs, normal types of WBCs, and lymphoblasts. The total number of RBCs and WBCs, along with classification …

Classifying Relations Using Recurrent Neural Network With Ontological-Concept Embedding, Mario J. Lorenzo

CCAC Theses and Dissertations

Relation extraction and classification represents a fundamental and challenging aspect of Natural Language Processing (NLP) research which depends on other tasks such as entity detection and word sense disambiguation. Traditional relation extraction methods based on pattern-matching using regular expressions grammars and lexico-syntactic pattern rules suffer from several drawbacks including the labor involved in handcrafting and maintaining large number of rules that are difficult to reuse. Current research has focused on using Neural Networks to help improve the accuracy of relation extraction tasks using a specific type of Recurrent Neural Network (RNN). A promising approach for relation classification uses an RNN …

Towards Practical Modulation Recognition For Future Spectrum-Sharing Applications, Wei Xiong

Legacy Theses & Dissertations (2009 - 2024)

With recent advances in emerging Dynamic Spectrum Access (DSA) and Cognitive Radio technologies, modulation recognition (ModRec) has emerged as a critical problem with importance to spectrum-sharing applications. Existing approaches, target modulation recognition as if a packet will be decoded in full and thus, pose stringent requirements on spectrum sensing and transmitter behavior: (i) a transmitter's bandwidth should be scanned alone and in full, (ii) for MIMO ModRec, the sensor should have at least same as many antennas as the transmitter, (iii) modulation symbol representation should be uniform and (iv) prior knowledge of the transmitter's technology should be available. These stringent …

Sequentially-Closed And Forward-Closed String Rewriting Systems, Yu Zhang

Legacy Theses & Dissertations (2009 - 2024)

In this dissertation we introduce the new concept of sequentially-closed string rewriting systems which generalizes forward-closed string rewriting systems and monadic string rewriting systems. We also investigate subclasses and properties of finite and regular sequentially-closed systems and forward-closed systems.

Detecting And Protecting Against Ai-Synthesized Faces, Yuezun Li

Legacy Theses & Dissertations (2009 - 2024)

The recent advances in deep learning and the availability of vast volume of online personal images and videos have drastically improved the reality of synthesized faces in images and videos. While there are interesting and creative applications of the AI face synthesis systems, they can also be weaponized, as it can create the illusions of a person's presence and activities that do not occur in reality, which results in serious political, social, financial, and legal consequences. Therefore, it is of great importance to develop effective method to expose the AI-synthesized faces. In this thesis, a set of our recent efforts …

Invariant-Based Online Software Anomaly Detection And Selective Regression Testing, Yizhen Chen

Legacy Theses & Dissertations (2009 - 2024)

Software has been extensively used in various domains to provide online services. With the growing popularity of these types of applications, the quality of the software has a great impact on many of our daily activities [1]. Reliable software executions that deliver expected outcomes are essential for quality services. Software is considered abnormal when its behavior deviates from what is expected at any point during its execution. When anomalous behavior propagates to an exit point of the software and produces an incorrect output or an unexpected termination of the execution, it is considered a software failure. An anomaly may or …

Uncertainty Learning In Subjective Logic And Pattern Discovery In Network Data, Adilijiang Alimu

Legacy Theses & Dissertations (2009 - 2024)

Uncertainty caused by unreliable or insufficient data and vulnerable machine learning models

Discriminative Factorization Models For Student Behavioral Pattern Detection And Classification, Mehrdad Mirzaei

Legacy Theses & Dissertations (2009 - 2024)

The goal of this dissertation is to examine factors such as how a student chooses to engage with the online platform and time spent on individual tasks and draw conclusions to improve the efficiency of the students and efficacy of online learning tools. Student activities and decision-making while functioning in a computer-based learning environment are utilized to guide students with effective patterns in studying. In addition to the sequence of actions, we have considered the time spent on each activity in modeling to have a more accurate representation of students' behavior in studying. Using sequential pattern mining methods, we find …

The Effects Of Mixed-Initiative Visualization Systems On Exploratory Data Analysis, Alvitta Ottley, Adam Kern

All Computer Science and Engineering Research

The primary purpose of information visualization is to act as a window between a user and the data. Historically, this has been accomplished via a single-agent framework: the only decision-maker in the relationship between visualization system and analyst is the analyst herself. Yet this framework arose not from first principles, but a necessity. Before this decade, computers were limited in their decision-making capabilities, especially in the face of large, complex datasets and visualization systems. This paper aims to present the design and evaluation of a mixed-initiative system that aids the user in handling large, complex datasets and dense visualization systems. …

Detecting Faces With Covid Protection Masks From Images Shot In Public Places Using Neural Networks, Hangkai Wang

Chulalongkorn University Theses and Dissertations (Chula ETD)

Since 2019, Covid-19 has become a common problem affecting all mankind. The disease has successfully spread all over the world. Wearing a mask can practically protect the infection. Thus, detecting people wearing and not wearing masks in public is essential. However, there is still some room to improve detection accuracy of the present methods. In this paper, the transfer learning model and FR-TSVM model are used to study the latest data of pneumonia epidemic situation in Covid-19. First, a data set of 11600 facial images wearing masks and not wearing masks in public was collected for training, testing, and validation. …

Hacking For Intelligence Collection In The Fight Against Terrorism: Israeli, Comparative, And International Perspectives, Asaf Lubin

Articles by Maurer Faculty

תקציר בעברית: הניסיון של המחוקק הישראלי להביא להסדרה מפורשת של סמכויות השב״כ במרחב הקיברנטי משקף מגמה רחבה יותר הניכרת בעולם לעיגון בחקיקה ראשית של הוראות בדבר פעולות פצחנות מצד גופי ביון ומודיעין ורשויות אכיפת חוק למטרות איסוף מודיעין לשם סיכול עבירות חמורות, ובייחוד עבירות טרור אם בעבר היו פעולות מסוג אלה כפופות לנהלים פנימיים ומסווגים, הרי שהדרישה לשקיפות בעידן שלאחר גילויי אדוארד סנודן מחד והשימוש הנרחב בתקיפות מחשב לביצוע פעולות חיפוש וחקירה לסיכול טרור מאידך, מציפים כעת את הדרישה להסמכה מפורשת. במאמר זה אבקש למפות הן את השדה הטכנולוגי והן את השדה המשפטי בכל האמור בתקיפות מחשבים למטרות ריגול ומעקב. …

Iot Devices In The Public Health Sector, Cayla Young

Cybersecurity Undergraduate Research Showcase

In this research, proper attention is drawn to privacy and security concerns with the integration of Internet of Things (IoT) devices in the public health sector. Often, not much attention is given to IoT devices and its vulnerabilities concerning the medical industry. Effects of COVID-19 contact tracing applications are explored through research of various source types. Mitigation techniques for these privacy and security issues is given. Focus is brought to topics outlining the risks associated with genetic testing companies and the vulnerabilities of data collection and data storage. Recommendations are provided to help consumers avoid these risks. Lastly, a comprehensive …

Fpga Based Blockchain System For Industrial Iot, Lei Xu, Lin Chen, Zhimin Gao, Hanyee Kim, Taeweon Suh, Weidong Shi

Computer Science Faculty Publications

Industrial IoT (IIoT) is critical for industrial infrastructure modernization and digitalization. Therefore, it is of utmost importance to provide adequate protection of the IIoT system. A modern IIoT system usually consists of a large number of devices that are deployed in multiple locations and owned/managed by different entities who do not fully trust each other. These features make it harder to manage the system in a coherent manner and utilize existing security mechanisms to offer adequate protection. The emerging blockchain technology provides a powerful tool for IIoT system management and protection because the IIoT nature of distributed deployment and involvement …