Computer Sciences Commons^™

Cybersecurity Strategy Against Cyber Attacks Towards Smart Grids With Pvs, Fangyu Li, Maria Valero, Liang Zhao, Yousef Mahmoud

KSU Proceedings on Cybersecurity Education, Research and Practice

Cyber attacks threaten the security of distribution power grids, such as smart grids. The emerging renewable energy sources such as photovoltaics (PVs) with power electronics controllers introduce new potential vulnerabilities. Based on the electric waveform data measured by waveform sensors in the smart grids, we propose a novel cyber attack detection and identification approach. Firstly, we analyze the cyber attack impacts (including cyber attacks on the solar inverter causing unusual harmonics) on electric waveforms in distribution power grids. Then, we propose a novel deep learning based mechanism including attack detection and attack diagnosis. By leveraging the electric waveform sensor data …

Wellstar Health Systems Internship- Cse 4983, Joyce Anderson, Project Advisor: Dawn Tatum

C-Day Computing Showcase

I interned at Wellstar Health Systems in there IT department. Staring from months 1 - 6 I rotated throughout the the IT Service Desk, Field Services, IT Service Management, IT Security, and IT Applications departments. Towards months 7 - 12 I worked in the IT Service management depart in the Knowledge based composing and editing knowledge articles for WellStar employees that had ITIL access to view and for instruction on how to work WellStar applications.

Global & Product Technology Intern Adp- Cs 7995, Neha Gosavi, Project Advisor: Dawn Tatum

C-Day Computing Showcase

I am Neha Gosavi. I am graduate student in Computer Science and currently doing summer internship as Global Product & Technology Intern at ADP. As intern I am part of SRE team(Site Reliability Engineer ).SRE team comprised of engineers taken from a diverse set of disciplines. This cross functional team was designed to support one of the key product offered by the company. I was involved with AWS cloud migration Poject and docker application, Splunk dashboard.

Improving Policy Making With Informed Covid-19 Case Prediction-Cs 4267, John Hurd, Project Advisor: Mohammed Aledhari

C-Day Computing Showcase

Covid-19 has necessitated many changes in the way life in the United States of America is lived. These include things such as new operational hours for retail and other service locations, mandatory and encouraged social distancing protocols on a state and federal level, and major changes to the way educational services are delivered in K-12 and higher education in both public and private contexts. The goal of this project is to produce a mathematical model with the express purpose of directly aiding pandemic response policy decision making by comparing predicted impacts of various logistical decisions and social distancing guidelines.

Web Developer Summer Intern At Keller Williams Realty- Cs 7995, Revatee Vaidya, Project Advisor: Dawn Tatum

C-Day Computing Showcase

The purpose of this poster is to outline the duties of a Summer intern at Keller Williams Realty in Atlanta, Georgia as a Web Developer Intern. At Keller Williams, my aim was to develop and design websites for Blue Apple Real Estate School and Blue Apple Homes using WordPress and Learn Dash. The poster discusses my summer training, projects I was involved in, Technologies I used and my future goals.

Global Product And Technology Intern, Adp- Cs 7995, Keerthi Manchukonda, Project Advisor: Dawn Tatum

C-Day Computing Showcase

I'm working on API for the PDF service generation of the Canadian Tax forms(Federal and Provinces) in specific. But it can be used for all countries and states.

Global Product And Technology Intern, Adp- Cs 7995, Deeksha Koya, Project Advisor: Dawn Tatum

C-Day Computing Showcase

Migrating the legacy surveys to on platform Salesforce Surveys.

Global Product And Technology Intern- Cs 7995, Krushita Patel, Project Advisor: Dawn Tatum

C-Day Computing Showcase

My project is about the experience that I have had and I have been currently having working as an intern at ADP working full time. I have also included my work description and what I am looking forward to for my rest of internship.

It Deployment And Fulfillment Co-Op- Cs 4983, Sam Wilson, Project Advisor: Dawn Tatum

C-Day Computing Showcase

No abstract provided.

Facial Recognition And Object Detection-Based Smart Cashier System- Cs 4732, Timmy Duong, Project Advisor: Mohammed Aledhari

C-Day Computing Showcase

The topic of smart based cashier system. Professor Dr. Aledhari is the project advisor for CS4732 Machine Vision.

Second Language Education Website And App Design, Songqiao Yu, Project Advisor: Mohammed Aledhari

C-Day Computing Showcase

During the pandemic, schools are closed and it brought a great chance for JoJo Learning to expand and explore the new method of customer acquisition. With a combination method of educational robot and E-book, JoJo is providing his customers with a compound solution for summer second language learning for kids and toddlers. As part of the team, my main responsibility is to prototype and publish new UIUX design and using data analysis as a method to find the key channels of the business.

Using Artificial Intelligence To Prescribe Medicine- Cs 4732, Xander Bush, Louis Livingston, Project Advisor: Mohammed Aledhari

C-Day Computing Showcase

With the current advancements being made in the Machine Learning field, utilizing Artificial Intelligence and Deep Learning techniques to analyze complex information such as genome information has become possible. By creating and building up a database of such data as well as compatible medicines, we suspect it is possible to prescribe personalized medicines to treat patients with a high percentage of success while also being able to take into account various other health conditions and pre-dispositions. This possibility depends heavily on the ability of the Neural Network or various other Machine Learning structure to correctly interpret the information from a …

Tracking High-Speed Chase Vehicles With Machine Learning​- Cs 4732, Louis Livingston, Dylan Sirna, Project Advisor: Mohammed Aledhari

C-Day Computing Showcase

From law enforcement officers, to fleeing suspects, to the general public, lengthy police pursuits poses a risk to all involved. With modern advances in machine vision, pursuits caught on camera can be analyzed with machine learning techniques. These techniques can then be used to produce datasets for future researchers to use in machine learning algorithms. This paper explores ways to produce those datasets using OpenCV, a machine vision library for Python, as well as GOTURN, a object tracker for OpenCV.

Service Industry Sentience- Cs 4267, Charles Peery, Project Advisor: Mohammed Aledhari

C-Day Computing Showcase

Since Amazon GO opened its' doors to employees in late 2016, businesses have been watching closely to see if a store without checkout can succeed in the current market.

While self-checkout stations have been in use since 1986, businesses are looking for ways to enhance the convenience of shoppers. From online ordering, contactless payments, and same day pickup, to drone delivery, leaving packages inside your home, and now checkout free stores.

In this presentation I explore the possibility of using YOLO and OpenCV to produce a checkout system based on object recognition which makes a system that is cheaper and …

Deep Learning For Identifying Breast Cancer, Yihong Li

Master of Science in Computer Science Theses

Medical images are playing an increasingly important role in the prevention and diagnosis of diseases. Medical images often contain massive amounts of data. Professional interpretation usually requires a long time of professional study and experience accumulation by doctors. Therefore, the use of super storage and computing power in deep learning as a basis can effectively process a large amount of medical data. Breast cancer brings great harm to female patients, and early diagnosis is the most effective prevention and treatment method, so this project will create a new optimized breast cancer auxiliary diagnosis model based on ResNet. Analyze and process, …

Deep Learning For Identifying Lung Diseases, Lin Wang

Master of Science in Computer Science Theses

Growing health problems, such as lung diseases, especially for children and the elderly, require better diagnostic methods, such as computer-based solutions, and it is crucial to detect and treat these problems early. The purpose of this article is to design and implement a new computer vision-based algorithm based on lung disease diagnosis, which has better performance in lung disease recognition than previous models to reduce lung-related health problems and costs . In addition, we have improved the accuracy of the five lung diseases detection, which helps doctors and doctors use computers to solve this problem at an early stage.

An Assessment Of Global Research Activities On Children And Adolescent Online Security, Adeola O. Opesade Dr, Omolayo A. Adesina Ms.

Journal of Cybersecurity Education, Research and Practice

The use of the Internet among children and adolescents is now a norm in many parts of the world. As the Internet offers a wide range of benefits to these ones, so does it expose them to possible various risks and harm. Researchers in different countries across the world have engaged in the production of relevant research-based knowledge in order to make the virtual world a safe place for the younger ones. However, while studies have been carried out on the subject of Internet risk among children and adolescents, there is a dearth of information on the assessment of research …

Evaluating And Securing Text-Based Java Code Through Static Code Analysis, Jeong Yang, Young Lee, Amanda Fernandez, Joshua Sanchez

Journal of Cybersecurity Education, Research and Practice

As the cyber security landscape dynamically evolves and security professionals work to keep apace, modern-day educators face the issue of equipping a new generation for this dynamic landscape. With cyber-attacks and vulnerabilities substantially increased over the past years in frequency and severity, it is important to design and build secure software applications from the group up. Therefore, defensive secure coding techniques covering security concepts must be taught from beginning computer science programming courses to exercise building secure applications. Using static analysis, this study thoroughly analyzed Java source code in two textbooks used at a collegiate level, with the goal of …

Malaware Defensive: A Game To Train Users To Combat Malware, Tyler Moon, Tamirat Abegaz, Bryson Payne, Abi Salimi

Journal of Cybersecurity Education, Research and Practice

Several research findings indicate that basic cyber hygiene can potentially deter the majority of cyber threats. One of the ways cybersecurity professionals can prepare users to ensure proper hygiene is to help them develop their ability to spot the difference between normal and abnormal behavior in a computer system. Malware disrupts the normal behavior of a computer system. The lack of appropriate user training has been one of the main reasons behind the exposure of computer systems to threats, from social engineering to viruses, trojans, and ransomware. Basic knowledge about common behavioral characteristics of malware could help users identify potentially …

Graphical Representation Of Text Semantics, Karl Kevin Tiba Fossoh

Master of Science in Computer Science Theses

A text is a set of words conveying a particular semantic based on their order, representation and structure. Those elements can be associated through a different set of interpretations, based on frequency and proportionality. The problem with context is that numbers do not help understand the semantics and fall short to convey the message of the text. The graphical representation of text semantics focuses on the conversion of text to images. Contrarily to word clouds that simply produce frequency mapping of words within the text and topic models that essentially give context to word frequencies and proportionalities, images keep intact …

Superb: Superior Behavior-Based Anomaly Detection Defining Authorized Users' Traffic Patterns, Daniel Karasek

Master of Science in Computer Science Theses

Network anomalies are correlated to activities that deviate from regular behavior patterns in a network, and they are undetectable until their actions are defined as malicious. Current work in network anomaly detection includes network-based and host-based intrusion detection systems. However, network anomaly detection schemes can suffer from high false detection rates due to the base rate fallacy. When the detection rate is less than the false positive rate, which is found in network anomaly detection schemes working with live data, a high false detection rate can occur. To overcome such a drawback, this paper proposes a superior behavior-based anomaly detection …

Data-Driven Investment Decisions In P2p Lending: Strategies Of Integrating Credit Scoring And Profit Scoring, Yan Wang

Doctor of Data Science and Analytics Dissertations

In this dissertation, we develop and discuss several loan evaluation methods to guide the investment decisions for peer-to-peer (P2P) lending. In evaluating loans, credit scoring and profit scoring are the two widely utilized approaches. Credit scoring aims at minimizing the risk while profit scoring aims at maximizing the profit. This dissertation addresses the strengths and weaknesses of each scoring method by integrating them in various ways in order to provide the optimal investment suggestions for different investors. Before developing the methods for loan evaluation at the individual level, we applied the state-of-the-art method called the Long Short Term Memory (LSTM) …

Fast Clustering Using A Grid-Based Underlying Density Function Approximation, Daniel Brown

Master of Science in Computer Science Theses

Clustering is an unsupervised machine learning task that seeks to partition a set of data into smaller groupings, referred to as “clusters”, where items within the same cluster are somehow alike, while differing from those in other clusters. There are many different algorithms for clustering, but many of them are overly complex and scale poorly with larger data sets. In this paper, a new algorithm for clustering is proposed to solve some of these issues. Density-based clustering algorithms use a concept called the “underlying density function”, which is a conceptual higher-dimension function that describes the possible results from the continuous …

Distributed Denial Of Service Attack Detection, Travis Blue

Master of Science in Information Technology Theses

Distributed Denial of Service (DDoS) attacks on web applications has been a persistent threat. Successful attacks can lead to inaccessible service to legitimate users in time and loss of business reputation. Most research effort on DDoS focused on network layer attacks. Existing approaches on application layer DDoS attack mitigation have limitations such as the lack of detection ability for low rate DDoS and not being able to detect attacks targeting resource files. In this work, we propose DDoS attack detection using concepts from information retrieval and machine learning. We include two popular concepts from information retrieval: Term Frequency (TF)-Inverse Document …

Divergent Student Views Of Cybersecurity, Susan E. Ramlo, John B. Nicholas

Journal of Cybersecurity Education, Research and Practice

Cybersecurity is a worldwide issue and concern. Prior studies indicate that many people do not use cybersecurity best practices. Although these prior studies used large-scale surveys or interviews, this study used Q methodology [Q] because Q provides greater insight than Likert-format surveys. In fact, Q was created to scientifically study subjectivity. Within a Q study, various stages as well as philosophical, epistemological, and ontological principles represent a complete methodology. At first, Q researchers collect items that represent the broad range of communications about the topic (called the concourse). Although the items can be pictures, scents, or other means of communication, …

Teaching About The Dark Web In Criminal Justice Or Related Programs At The Community College And University Levels., Scott H. Belshaw, Brooke Nodeland, Lorrin Underwood, Alexandrea Colaiuta

Journal of Cybersecurity Education, Research and Practice

Increasingly, criminal justice practitioners have been called on to help solve breaches in cyber security. However, while the demand for criminal justice participation in cyber investigations increases daily, most universities are lagging in their educational and training opportunities for students entering the criminal justice fields. This article discusses the need to incorporate courses discussing the Dark Web in criminal justice. A review of existing cyber-criminal justice programs in Texas and nationally suggests that most community colleges and 4-year universities have yet to develop courses/programs in understanding and investigating the Dark Web on the internet. The Dark Web serves as the …

An Assessment Of Practical Hands-On Lab Activities In Network Security Management, Te-Shun Chou, Nicholas Hempenius

Journal of Cybersecurity Education, Research and Practice

With the advancement in technology over the past decades, networks have become increasingly large and complex. In the meantime, cyberattacks have become highly sophisticated making them difficult to detect. These changes make securing a network more challenging than ever before. Hence, it is critical to prepare a comprehensive guide of network security management for students assist them in becoming network security professionals.

The objective of this paper is to introduce a variety of techniques related to network security management, such as Simple Network Management Protocol (SNMP), event management, security policy management, risk management, access control, and remote monitoring. With the …

Fusion-Net: Integration Of Dimension Reduction And Deep Learning Neural Network For Image Classification, Mohammad Masum, Philippe Laval

Published and Grey Literature from PhD Candidates

Building a deep network using original digital images requires learning many parameters which may reduce the accuracy rates. The images can be compressed by using dimension reduction methods and extracted reduced features can be feeding into a deep network for classification. Hence, in the training phase of the network, the number of parameters will be decreased. Principal Component Analysis is a well-known dimension reduction technique that leverage orthogonal linear transformation of the original data. In this paper, we propose a neural network-based framework, named Fusion-Net, which implements PCA on an image dataset (CIFAR-10) and then a neural network applies on …

Editorial

Journal of Cybersecurity Education, Research and Practice

Editorial.

Editorial, Michael E. Whitman, Herbert J. Mattord, Hossain Shahriar

Journal of Cybersecurity Education, Research and Practice

No abstract provided.