Operationalizing Deterrence By Denial In The Cyber Domain,
2023
University of South Florida
Operationalizing Deterrence By Denial In The Cyber Domain, Gentry Lane
Military Cyber Affairs
No abstract provided.
Improvements To Passive Fingerprinting Of Operational Technology Environments,
2023
Boise State University
Improvements To Passive Fingerprinting Of Operational Technology Environments, Lawrence Wellman
Cyber Operations and Resilience Program Graduate Projects
This paper explores the effectiveness of three network tools for analyzing network traffic and highlights their reliance on network ports to fingerprint TCP and UDP network protocols. Considering this limitation, the paper introduces protoDetect, a novel tool demonstrating a possible solution for identifying Operational Technology (OT) network protocols.
Effects Of Factors On The Market Price Of The Shares Using Design Of Experiment,
2023
Department of Mathematical Sciences, Islamic University of Science and Technology, Pulwana, India
Effects Of Factors On The Market Price Of The Shares Using Design Of Experiment, Amir Ahmad Dar, Mohammad Shahfaraz Khan, Imran Azad, Tanveer Ahmad Tarray, N. Anuradha, Qaiser Farroq Dar
Applied Mathematics & Information Sciences
When the cost of capital, dividends and the price of the share at the beginning is known, Modigliani and Miller’s model can be used to estimate the price of the share at the end of the period. A design of experiment (Taguchi’s orthogonal array) is used in order to investigate the impact of three parameters on the price of the share at the end of the period. The main aim of this research article is to find which parameter is more significant on the price of the share at the end of the period. Taguchi’s methodology of design of the …
Enabling High Throughput And Reliable Low Latency Communication Over Vehicular Mobility In Next-Generation Cellular Networks,
2023
Clemson University
Enabling High Throughput And Reliable Low Latency Communication Over Vehicular Mobility In Next-Generation Cellular Networks, Snigdhaswin Kar
All Dissertations
The fifth-generation (5G) networks and beyond need paradigm shifts to realize the exponentially increasing demands of next-generation services for high throughputs, low latencies, and reliable communication under various mobility scenarios. However, these promising features have critical gaps that need to be filled before they can be fully implemented for mobile applications in complex environments like smart cities. Although the sub-6 GHz bands can provide reliable and larger coverage, they cannot provide high data rates with low latencies due to a scarcity of spectrum available in these bands. Millimeter wave (mmWave) communication is a key enabler for a significant increase in …
Preserving User Data Privacy Through The Development Of An Android Solid Library,
2023
University of Arkansas, Fayetteville
Preserving User Data Privacy Through The Development Of An Android Solid Library, Alexandria Lim
Computer Science and Computer Engineering Undergraduate Honors Theses
In today’s world where any and all activity on the internet produces data, user data privacy and autonomy are not prioritized. Companies called data brokers are able to gather data elements of personal information numbering in the billions. This data can be anything from purchase history, credit card history, downloaded applications, and service subscriptions. This information can be analyzed and inferences can be drawn from analysis, categorizing people into groups that range in sensitivity — from hobbies to race and income classes. Not only do these data brokers constantly overlook data privacy, this mass amount of data makes them extremely …
Critical Infrastructure Workforce Development Pods For Teaching Cybersecurity Using Netlab+,
2023
University of Arkansas, Fayetteville
Critical Infrastructure Workforce Development Pods For Teaching Cybersecurity Using Netlab+, Gideon Sutterfield
Computer Science and Computer Engineering Undergraduate Honors Theses
As digital automation for Industrial Control Systems has grown, so has its vulnerability to cyberattacks. The world of industry has responded effectively to this, but the world of academia is still lagging as its emphasis is still almost entirely on information technology. Considering this, we created a workforce development pod that serves as a hands-on learning module for teaching students key cybersecurity ideas surrounding operational technology using the NETLAB+ platform. A pod serves as the virtual environment where the learning exercise takes place. This project’s implementation involved the creation of a segmented network within the pod where a student starts …
Protecting The Infrastructure Of Michigan: Analyzing And Understanding Internet Infrastructure,
2023
University of Nebraska at Omaha
Protecting The Infrastructure Of Michigan: Analyzing And Understanding Internet Infrastructure, Samuel Blaser, Travis Munyer, Damian Ramirez, Lester Juarez, Jackson Servant
Theses/Capstones/Creative Projects
The Michigan Army National Guard DCOE is hoping to increase their understanding of the physical, electrical, protocol, and logical topography of internet service. In order to understand the infrastructure of the internet, information must be collected on its pieces. By studying, describing, and illustrating the infrastructure of the global internet we can develop hardening tactics, improve user training, and develop contingency plans in the case of an attack. The research is focused on where data lives, locating data centers in the region, identifying global infrastructure and who owns it, and potential for hardening. An interactive map has been created in …
The Rapid Increase Of Ransomware Attacks Over The 21st Century And Mitigation Strategies To Prevent Them From Arising,
2023
Liberty University
The Rapid Increase Of Ransomware Attacks Over The 21st Century And Mitigation Strategies To Prevent Them From Arising, Sanjay Jacob
Senior Honors Theses
Cyber-attacks have continued to become more common throughout the past century as more people are exposed to the Internet. Every year, various studies, reports, and scholarly research is done to emphasis the rapid increase of attacks. In this honors thesis, the student sought to gather further information about the rise of ransomware attacks, various cyber threats, discuss the psychological manipulation that exist, and provided the reader with an ethical complement of cyber-attacks. Additionally, case studies from previous research have been analyzed and mitigation strategies have been explained to provide the reader with practical application. This research emphasizes in on key …
Iot Health Devices: Exploring Security Risks In The Connected Landscape,
2023
University of Tartu
Iot Health Devices: Exploring Security Risks In The Connected Landscape, Abasi-Amefon Obot Affia, Hilary Finch, Woosub Jung, Issah Abubakari Samori, Lucas Potter, Xavier-Lewis Palmer
School of Cybersecurity Faculty Publications
The concept of the Internet of Things (IoT) spans decades, and the same can be said for its inclusion in healthcare. The IoT is an attractive target in medicine; it offers considerable potential in expanding care. However, the application of the IoT in healthcare is fraught with an array of challenges, and also, through it, numerous vulnerabilities that translate to wider attack surfaces and deeper degrees of damage possible to both consumers and their confidence within health systems, as a result of patient-specific data being available to access. Further, when IoT health devices (IoTHDs) are developed, a diverse range of …
Vanet Applications Under Loss Scenarios & Evolving Wireless Technology,
2023
Clemson University
Vanet Applications Under Loss Scenarios & Evolving Wireless Technology, Adil Alsuhaim
All Dissertations
In this work we study the impact of wireless network impairment on the performance of VANET applications such as Cooperative Adaptive Cruise Control (CACC), and other VANET applications that periodically broadcast messages. We also study the future of VANET application in light of the evolution of radio access technologies (RAT) that are used to exchange messages. Previous work in the literature proposed fallback strategies that utilizes on-board sensors to recover in case of wireless network impairment, those methods assume a fixed time headway value, and do not achieve string stability. In this work, we study the string stability of a …
Enhanced Mobile Networking Using Multi-Connectivity And Packet Duplication In Next-Generation Cellular Networks,
2023
Clemson University
Enhanced Mobile Networking Using Multi-Connectivity And Packet Duplication In Next-Generation Cellular Networks, Prabodh Mishra
All Dissertations
Modern cellular communication systems need to handle an enormous number of users and large amounts of data, including both users as well as system-oriented data. 5G is the fifth-generation mobile network and a new global wireless standard that follows 4G/LTE networks. The uptake of 5G is expected to be faster than any previous cellular generation, with high expectations of its future impact on the global economy. The next-generation 5G networks are designed to be flexible enough to adapt to modern use cases and be highly modular such that operators would have the flexibility to provide selective features based on user …
Intelligent And Explainable Solution To Predict Infant Birthweight And Preterm Birth In The United Arab Emirates,
2023
United Arab Emirates University
Intelligent And Explainable Solution To Predict Infant Birthweight And Preterm Birth In The United Arab Emirates, Wasif Khan
Dissertations
Adverse pregnancy outcomes such as Low Birth Weight (LBW) and Preterm birth (PTB) are complex pregnancy challenges that can lead to high perinatal mortality and long-term morbidity for infants. Early prediction of such adverse outcomes can be useful for averting catastrophic outcomes for the mother and her baby. With advances in machine learning (ML)-based algorithms, several models have been proposed for both PTB and LBW predictions. However, the risk factors associated with these outcomes are still unknown, particularly in the United Arab Emirates (UAE). Furthermore, existing ML-based prediction models work in a black-box manner and lack proper interpretations for clinicians, …
Bridging The Gap Between Public Organizaions And Cybersecurity,
2023
California State University, San Bernardino
Bridging The Gap Between Public Organizaions And Cybersecurity, Christopher Boutros
Electronic Theses, Projects, and Dissertations
Cyberattacks are a major problem for public organizations across the nation, and unfortunately for them, the frequency of these attacks is constantly growing. This project used a case study approach to explore the types of cybersecurity public organization agencies face and how those crimes can be mitigated. The goal of this paper is to understand how public organization agencies have prepared for cyberattacks and discuss additional suggestions to improve their current systems with the current research available This research provides an analysis of current cyber security systems, new technologies that can be implemented, roadblocks public agencies face before and during …
Methods And Algorithms For Monitoring And Prediction Of Various Fire Hazardous Situations,
2023
Tashkent University of Information Technologies Tashkent, Uzbekistan. E-mail: [email protected];
Methods And Algorithms For Monitoring And Prediction Of Various Fire Hazardous Situations, Mizaakbar Xakkulmirzayevich Hudayberdiyev, Oybek Zokirovich Koraboshev
Chemical Technology, Control and Management
This article analyzes emergency situations arising from natural disasters (fires, explosions, earthquakes, floods, landslides, etc.) and man-made accidents. The event in which the values of fire risks in the area decrease uniformly and at the same time the amount of fire risks is minimal is considered optimal. Models, methods, and logistic regression algorithm have been used to predict fire hazard situations and identify potential fire safety measures.
Encrypted Malicious Network Traffic Detection Using Machine Learning,
2023
Kennesaw State University
Encrypted Malicious Network Traffic Detection Using Machine Learning, Niklas Knipschild
Symposium of Student Scholars
The research project aims to find ways to detect malicious packets inside encrypted network traffic. In addition to this goal maintaining user privacy is a priority. As encryption has become less expensive to implement more and more network traffic is encrypted. Currently, 90% of all network traffic is encrypted, and this trend is expected to increase. The creators of malware areemploying various methods to ensure delivery of their malware, including encryption. One proposed method to combat this suggests implementing machine learning with various algorithms to analyze packet attributes to determine if they contain malware, without actually knowing what's inside …
Models Of Team Structure In Information Security Incident Investigation,
2023
TUIT named after Muhammad al-Khwarazmi. Address: 108, Amir Temur st., Tashkent city, Republic of Uzbekistan. E-mail: [email protected], Phone:+998-97-751-16-97.
Models Of Team Structure In Information Security Incident Investigation, Fayzullajon Botirov
Chemical Technology, Control and Management
This article discusses the models of the group structure in the investigation of information security incidents, contradictions in the investigation of information security incidents, methods for assessing information security incidents at the enterprise, processes for assessing information security incidents based on its factors.
Detection Optimization Of Rare Attacks In Software-Defined Network Using Ensemble Learning,
2023
Canadian International College, Cairo, Egypt
Detection Optimization Of Rare Attacks In Software-Defined Network Using Ensemble Learning, Ahmed M. El-Shamy, Nawal A. El-Fishawy, Gamal M. Attiya, Mokhtar Ahmed
Mansoura Engineering Journal
Software-defined networking (SDN) is a highly flexible architecture that automates and facilitates network configuration and management. Intrusion detection systems (IDS) are becoming essential components in the network to detect malicious attacks and suspicious activities by continuously monitoring network traffic. Integration between SDN and machine learning (ML) techniques is extensively used to build an effective IDS against all potential cyber-attacks that aim at breaking the network security policy and stealing valuable data. Implementing an IDS based on SDN and ML has the advantage of managing traffic dynamically and fully autonomously to provide high protection against security threats. The main objective of …
Ransomware: What Is Ransomware, And How To Prevent It,
2023
Old Dominion University
Ransomware: What Is Ransomware, And How To Prevent It, Brandon Chambers
Cybersecurity Undergraduate Research Showcase
This research paper answers the question, “What is Ransomware, and How to prevent it?”. This paper will discuss what ransomware is, its history about ransomware, how ransomware attacks Windows systems, how to prevent ransomware, how to handle ransomware once it is already on the network, ideas for training professionals to avoid ransomware, and how anti-virus helps defend against ransomware. Many different articles, case studies, and professional blogs will be used to complete the research on this topic.
Proposed Mitigation Framework For The Internet Of Insecure Things,
2023
Prof. & head of Communications & Computer Engineering Department, MET academy, Mansoura, Egypt.
Proposed Mitigation Framework For The Internet Of Insecure Things, Mahmoud M. Elgindy, Sally M. Elghamrawy, Ali I. El-Desouky
Mansoura Engineering Journal
Intrusion detection systems IDS are increasingly utilizing machine learning methods. IDSs are important tools for ensuring the security of network data and resources. The Internet of Things (IoT) is an expanding network of intelligent machines and sensors. However, they are vulnerable to attackers because of the ubiquitous and extensive IoT networks. Datasets from intrusion detection systems (IDS) have been analyzed deep learning methods such as Bidirectional long-short term memory (BiLSTM). This research presents an BiLSTM intrusion detection framework with Principal Component Analysis PCA (PCA-LSTM-IDS). The PCA-LSTM-IDS is comprised of two layers: extracting layer which using PCA, and the anomaly BiLSTM …
Leveraging Artificial Intelligence And Machine Learning For Enhanced Cybersecurity: A Proposal To Defeat Malware,
2023
Old Dominion University
Leveraging Artificial Intelligence And Machine Learning For Enhanced Cybersecurity: A Proposal To Defeat Malware, Emmanuel Boateng
Cybersecurity Undergraduate Research Showcase
Cybersecurity is very crucial in the digital age in order to safeguard the availability, confidentiality, and integrity of data and systems. Mitigation techniques used in the industry include Multi-factor Authentication (MFA), Incident Response Planning (IRP), Security Information and Event Management (SIEM), and Signature-based and Heuristic Detection.
MFA is employed as an additional layer of protection in several sectors to help prevent unauthorized access to sensitive data. IRP is a plan in place to address cybersecurity problems efficiently and expeditiously. SIEM offers real-time analysis and alerts the system of threats and vulnerabilities. Heuristic-based detection relies on detecting anomalies when it comes …
