Analysis Of Theoretical And Applied Machine Learning Models For Network Intrusion Detection,
2021
Dakota State University
Analysis Of Theoretical And Applied Machine Learning Models For Network Intrusion Detection, Jonah Baron
Masters Theses & Doctoral Dissertations
Network Intrusion Detection System (IDS) devices play a crucial role in the realm of network security. These systems generate alerts for security analysts by performing signature-based and anomaly-based detection on malicious network traffic. However, there are several challenges when configuring and fine-tuning these IDS devices for high accuracy and precision. Machine learning utilizes a variety of algorithms and unique dataset input to generate models for effective classification. These machine learning techniques can be applied to IDS devices to classify and filter anomalous network traffic. This combination of machine learning and network security provides improved automated network defense by developing highly-optimized …
A Framework To Detect The Susceptibility Of Employees To Social Engineering Attacks,
2021
Embry-Riddle Aeronautical University
A Framework To Detect The Susceptibility Of Employees To Social Engineering Attacks, Hashim H. Alneami
Doctoral Dissertations and Master's Theses
Social engineering attacks (SE-attacks) in enterprises are hastily growing and are becoming increasingly sophisticated. Generally, SE-attacks involve the psychological manipulation of employees into revealing confidential and valuable company data to cybercriminals. The ramifications could bring devastating financial and irreparable reputation loss to the companies. Because SE-attacks involve a human element, preventing these attacks can be tricky and challenging and has become a topic of interest for many researchers and security experts. While methods exist for detecting SE-attacks, our literature review of existing methods identified many crucial factors such as the national cultural, organizational, and personality traits of employees that enable …
A Deep Learning-Based Automatic Object Detection Method For Autonomous Driving Ships,
2021
University of Southern Mississippi
A Deep Learning-Based Automatic Object Detection Method For Autonomous Driving Ships, Ojonoka Erika Atawodi
Master's Theses
An important feature of an Autonomous Surface Vehicles (ASV) is its capability of automatic object detection to avoid collisions, obstacles and navigate on their own.
Deep learning has made some significant headway in solving fundamental challenges associated with object detection and computer vision. With tremendous demand and advancement in the technologies associated with ASVs, a growing interest in applying deep learning techniques in handling challenges pertaining to autonomous ship driving has substantially increased over the years.
In this thesis, we study, design, and implement an object recognition framework that detects and recognizes objects found in the sea. We first curated …
On Utilizing Prunable Blockchains For Secure Message Dissemination In Vanets,
2021
East Tennessee State University
On Utilizing Prunable Blockchains For Secure Message Dissemination In Vanets, Edgar Bowlin Iii`
Undergraduate Honors Theses
Blockchain's use in Vehicular Ad-Hoc Networks (VANETs) research demonstrates that the technology provides useful attributes to allow for the safe and secure operation of VANET applications. The growth of blockchain applications pose a threat to the efficient operation of the MANET-like environment found within VANETs. Floating Genesis Blocks (FGB) can be used to preserve the state of the blockchain up to a certain point, and allows for the safe pruning of the chain without information loss. The early work presented here demonstrates two pruning techniques and compares the effects of each blockchain through simulation measurement of the chain's space requirements. …
A Deep Analysis And Algorithmic Approach To Solving Complex Fitness Issues In Collegiate Student Athletes,
2021
Georgia Southern University
A Deep Analysis And Algorithmic Approach To Solving Complex Fitness Issues In Collegiate Student Athletes, Holly N. Puckett
Honors College Theses
Sports are not simply an entertainment source. For many, it creates a sense of community, support, and trust among both fans and athletes alike. In order to continue the sense of community sports provides, athletes must be properly cared for in order to perform at the highest level possible. Thus, their fitness and health must be monitored continuously. In a professional sense, one can expect individualized attention to athletes daily due to an abundance of funding and resources. However, when looking at college communities and student athletes within them, the number of athletes per athletic trainer increases due to both …
Implications Of The Quantum Dna Model For Information Sciences,
2021
University of Tennessee Health Science Center
Implications Of The Quantum Dna Model For Information Sciences, F. Matthew Mihelic
Faculty Publications
The DNA molecule can be modeled as a quantum logic processor, and this model has been supported by pilot research that experimentally demonstrated non-local communication between cells in separated cell cultures. This modeling and pilot research have important implications for information sciences, providing a potential architecture for quantum computing that operates at room temperature and is scalable to millions of qubits, and including the potential for an entanglement communication system based upon the quantum DNA architecture. Such a system could be used to provide non-local quantum key distribution that could not be blocked by any shielding or water depth, would …
Prediction Of Days-On-Market For Single-Family Homes In The Housing Market Of Savannah,
2021
Georgia Southern University
Prediction Of Days-On-Market For Single-Family Homes In The Housing Market Of Savannah, Keagan Galbraith
Honors College Theses
The number of days that a home stays on the housing market (Days-On-Market—DOM) provides crucial information about the real estate market’s behavior that affects the buyer’s/seller’s decision (at the micro-level) and indicates the level of risk associated with real estate investments and identifies the housing bubbles (at the macro level). Housing data has a mixture of simple and complex attributes. A complex attribute in contrast with a simple attribute, has an array of values for a real estate property, which creates a major challenge in prediction of DOM. DOM is a binary attribute with values of “short” (£ six months) …
Iot Based Agriculture 4.0: Challenges And Opportunities,
2021
Tashkent University of Information Technologies
Iot Based Agriculture 4.0: Challenges And Opportunities, Halimjon Khujamatov, Temur Toshtemirov Mr., Doston Turayevich Khasanov Mr., Nasiba Saburova Ms., Ilhom Ikromovich Xamroyev Mr.
Bulletin of TUIT: Management and Communication Technologies
In recent years, the world's population growth has been intensifying, resulting in specific problems related to the depletion of natural resources, food shortages, declining fertile lands, and changing weather conditions. This paper has been discussed the use of IoT technology as a solution to such problems.
At the same time, the emergence of IoT technology has given rise to a new research direction in agriculture. Soil analysis and monitoring using Zigbee wireless sensor network technology, which is part of the IoT, will enable the creation of an IoT ecosystem as well as the development of smart agriculture. In addition, entrepreneurship, …
Interrupting The Propaganda Supply Chain,
2021
Technological University Dublin
Interrupting The Propaganda Supply Chain, Kyle Hamilton, Bojan Bozic, Luc Longo
Conference papers
In this early-stage research, a multidisciplinary approach is presented for the detection of propaganda in the media, and for modeling the spread of propaganda and disinformation using semantic web and graph theory. An ontology will be designed which has the theoretical underpinnings from multiple disciplines including the social sciences and epidemiology. An additional objective of this work is to automate triple extraction from unstructured text which surpasses the state-of-the-art performance.
Network-Based Analysis Of Early Pandemic Mitigation Strategies: Solutions, And Future Directions,
2021
Syracuse University
Network-Based Analysis Of Early Pandemic Mitigation Strategies: Solutions, And Future Directions, Pegah Hozhabrierdi, Raymond Zhu, Maduakolam Onyewu, Sucheta Soundarajan
Northeast Journal of Complex Systems (NEJCS)
Despite the large amount of literature on mitigation strategies for pandemic spread, in practice, we are still limited by naive strategies, such as lockdowns, that are not effective in controlling the spread of the disease in long term. One major reason behind adopting basic strategies in real-world settings is that, in the early stages of a pandemic, we lack knowledge of the behavior of a disease, and so cannot tailor a more sophisticated response. In this study, we design different mitigation strategies for early stages of a pandemic and perform a comprehensive analysis among them. We then propose a novel …
Optimizing Networking Topologies With Shortest Path Algorithms,
2021
University of Nebraska at Omaha
Optimizing Networking Topologies With Shortest Path Algorithms, Jordan Sahs
UNO Student Research and Creative Activity Fair
Communication networks tend to contain redundant devices and mediums of transmission, thus the need to locate, document, and optimize networks is increasingly becoming necessary. However, many people do not know where to start the optimization progress. What is network topology? What is this “Shortest Path Problem”, and how can it be used to better my network? These questions are presented, taught, and answered within this paper. To supplement the reader’s understanding there are thirty-eight figures in the paper that are used to help convey and compartmentalize the learning process needed to grasp the materials presented in the ending sections.
In …
Analysis Of System Performance Metrics Towards The Detection Of Cryptojacking In Iot Devices,
2021
Dakota State University
Analysis Of System Performance Metrics Towards The Detection Of Cryptojacking In Iot Devices, Richard Matthews
Masters Theses & Doctoral Dissertations
This single-case mechanism study examined the effects of cryptojacking on Internet of Things (IoT) device performance metrics. Cryptojacking is a cyber-threat that involves stealing the computational resources of devices belonging to others to generate cryptocurrencies. The resources primarily include the processing cycles of devices and the additional electricity needed to power this additional load. The literature surveyed showed that cryptojacking has been gaining in popularity and is now one of the top cyberthreats. Cryptocurrencies offer anyone more freedom and anonymity than dealing with traditional financial institutions which make them especially attractive to cybercriminals. Other reasons for the increasing popularity of …
Analyzing The Effectiveness Of Legal Regulations And Social Consequences For Securing Data,
2021
Dakota State Universi
Analyzing The Effectiveness Of Legal Regulations And Social Consequences For Securing Data, Howard B. Goodman
Masters Theses & Doctoral Dissertations
There is a wide range of concerns and challenges related to stored data security – which range from privacy and management to operations readiness, These challenges span from financial to personal and public impact. With an abundance of regulations for the enforcement of data security and emerging requirements proposed every year, organizations cannot avoid the legal or social implications of inadequate data protection. Today, public spotlight and awareness are challenging organizations to enhance how data is protected more than at any other time. For this reason, organizations have made significant efforts to improve security.
When looking at precautions or changes, …
Survey On Quantum Circuit Compilation For Noisy Intermediate-Scale Quantum Computers: Artificial Intelligence To Heuristics,
2021
CUNY New York City College of Technology
Survey On Quantum Circuit Compilation For Noisy Intermediate-Scale Quantum Computers: Artificial Intelligence To Heuristics, Janusz Kusyk, Samah Mohamed Saeed, Muharrem Umit Uyar
Publications and Research
Computationally expensive applications, including machine learning, chemical simulations, and financial modeling, are promising candidates for noisy intermediate scale quantum (NISQ) computers. In these problems, one important challenge is mapping a quantum circuit onto NISQ hardware while satisfying physical constraints of an underlying quantum architecture. Quantum circuit compilation (QCC) aims to generate feasible mappings such that a quantum circuit can be executed in a given hardware platform with acceptable confidence in outcomes. Physical constraints of a NISQ computer change frequently, requiring QCC process to be repeated often. When a circuit cannot directly be executed on a quantum hardware due to its …
Scite: The Next Generation Of Citations,
2021
Murray State University
Scite: The Next Generation Of Citations, Sean Rife, Domenic Rosati, Joshua M. Nicholson
Faculty & Staff Research and Creative Activity
Key points
- While the importance of citation context has long been recognized, simple citation counts remain as a crude measure of importance.
- Providing citation context should support the publication of careful science instead of headline‐grabbing and salami‐sliced non‐replicable studies.
- Machine learning has enabled the extraction of citation context for the first time, and made the classification of citation types at scale possible.
Using A Hybrid Agent-Based And Equation Based Model To Test School Closure Policies During A Measles Outbreak,
2021
Technological University Dublin
Using A Hybrid Agent-Based And Equation Based Model To Test School Closure Policies During A Measles Outbreak, Elizabeth Hunter, John D. Kelleher
Articles
Background
In order to be prepared for an infectious disease outbreak it is important to know what interventions will or will not have an impact on reducing the outbreak. While some interventions might have a greater effect in mitigating an outbreak, others might only have a minor effect but all interventions will have a cost in implementation. Estimating the effectiveness of an intervention can be done using computational modelling. In particular, comparing the results of model runs with an intervention in place to control runs where no interventions were used can help to determine what interventions will have the greatest …
Block The Root Takeover: Validating Devices Using Blockchain Protocol,
2021
Dakota State University
Block The Root Takeover: Validating Devices Using Blockchain Protocol, Sharmila Paul
Masters Theses & Doctoral Dissertations
This study addresses a vulnerability in the trust-based STP protocol that allows malicious users to target an Ethernet LAN with an STP Root-Takeover Attack. This subject is relevant because an STP Root-Takeover attack is a gateway to unauthorized control over the entire network stack of a personal or enterprise network. This study aims to address this problem with a potentially trustless research solution called the STP DApp. The STP DApp is the combination of a kernel /net modification called stpverify and a Hyperledger Fabric blockchain framework in a NodeJS runtime environment in userland. The STP DApp works as an Intrusion …
A Consent Framework For The Internet Of Things In The Gdpr Era,
2021
Dakota State University
A Consent Framework For The Internet Of Things In The Gdpr Era, Gerald Chikukwa
Masters Theses & Doctoral Dissertations
The Internet of Things (IoT) is an environment of connected physical devices and objects that communicate amongst themselves over the internet. The IoT is based on the notion of always-connected customers, which allows businesses to collect large volumes of customer data to give them a competitive edge. Most of the data collected by these IoT devices include personal information, preferences, and behaviors. However, constant connectivity and sharing of data create security and privacy concerns. Laws and regulations like the General Data Protection Regulation (GDPR) of 2016 ensure that customers are protected by providing privacy and security guidelines to businesses. Data …
Cybersecurity Education For Non-Technical Learners,
2021
Dakota State University
Cybersecurity Education For Non-Technical Learners, Matthew Mcnulty
Masters Theses & Doctoral Dissertations
Today’s world is increasingly reliant on technology for school, work, entertainment, and general home use. Many jobs today could not be performed without the use of computer systems or other technology. As lives become intertwined with technology, everyone will inevitably encounter malicious, vulnerable, or privacy-compromising devices or services. Unfortunately, knowledge of how to deal with these cybersecurity and privacy issues is not something that falls within the domain of common knowledge for the everyday person. Additionally, there is a lack of work being done to understand the educational needs of various groups within the general public and educate them. This …
Jrevealpeg: A Semi-Blind Jpeg Steganalysis Tool Targeting Current Open-Source Embedding Programs,
2021
Dakota State University
Jrevealpeg: A Semi-Blind Jpeg Steganalysis Tool Targeting Current Open-Source Embedding Programs, Charles A. Badami
Masters Theses & Doctoral Dissertations
Steganography in computer science refers to the hiding of messages or data within other messages or data; the detection of these hidden messages is called steganalysis. Digital steganography can be used to hide any type of file or data, including text, images, audio, and video inside other text, image, audio, or video data. While steganography can be used to legitimately hide data for non-malicious purposes, it is also frequently used in a malicious manner. This paper proposes JRevealPEG, a software tool written in Python that will aid in the detection of steganography in JPEG images with respect to identifying a …
