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- Technocentric mythos bias; cybersecurity incident attribution; end-user attribution; socio-technical systems; technical debt; secure systems engineering; component security; cybersecurity governance; attribution bias; causality framework; cybersecurity ontology and taxonomy (1)
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Articles 1 - 9 of 9
Full-Text Articles in Risk Analysis
Stop Blaming My Users: Illumination Of The Technocentric Mythos Bias, Ervin H. Frenzel, Richard Lightcap
Stop Blaming My Users: Illumination Of The Technocentric Mythos Bias, Ervin H. Frenzel, Richard Lightcap
Journal of Cybersecurity Education, Research and Practice
Abstract -This conceptual essay addresses the need for systemic and systematic transdisciplinary analytical techniques within cybersecurity and technical security. This conceptual essay is contingent upon recognition that cybersecurity is not simply technical in nature, it does not need an adversary, and more importantly it is based upon systems engineering and systems thinking. The essay contributes a socio-technical attribution chain and field-specific ontology/taxonomy which distinguish user-triggered events from root causes, latent conditions, technical debt, validation failures, governance failures, and attribution bias before assigning responsibility to end users. It systematically defines an ontology inclusive of developer technical debt, organizational debt arising from …
Kennesaw State University Student Managed Investment Fund Sector Sensitivity Analysis, John Kiersznowski, Joe Johnson, Kyler Howell, Geranger Lewis
Kennesaw State University Student Managed Investment Fund Sector Sensitivity Analysis, John Kiersznowski, Joe Johnson, Kyler Howell, Geranger Lewis
Senior Design Project For Engineers
The Kennesaw State University Student Managed Investment Fund (SMIF) Sector Sensitivity Analysis focuses on improving the fund’s decision-making and performance through data science. The SMIF is a diversified index fund designed to outperform indices like the S&P 500. This project investigates how macroeconomic variables—such as GDP growth, inflation, interest rates, and commodity prices—impact sector performance. By structuring data, developing a sustainable data pipeline, and leveraging advanced statistical techniques and predictive modeling, our team was able to provide the framework and proof of actionable insights that enhance the fund's ability to manage risks and optimize returns.
Medical Imaging Dataset Management Leveraging Deep Learning Frameworks In Breast Cancer Screening, Inchan Hwang
Medical Imaging Dataset Management Leveraging Deep Learning Frameworks In Breast Cancer Screening, Inchan Hwang
Dissertations
In the domain of Computer-Aided Diagnosis (CADx) for breast cancer diagnosis through mammography, prevailing models have traditionally been trained and validated using old film-based mammography. However, contemporary U.S. hospital practices involve the utilization of Full Field Digital Mammography (FFDM), offering more detailed images captured at various angles than old film-scanned mammography. Despite this shift, the existing body of research predominantly focuses on old-film based datasets, the implications of FFDM for CADx systems have not been understood. This dissertation addresses the issues emerged from FFDM such as data augmentation between old film-based set and new FFDM whether they are more effective …
Kwad - Ksu All Weather Autonomous Drone, Nick Farinacci, Sebastian Gomez, Stewart Baker, Ed Sheridan
Kwad - Ksu All Weather Autonomous Drone, Nick Farinacci, Sebastian Gomez, Stewart Baker, Ed Sheridan
Symposium of Student Scholars
"KWAD" or "KSU all-Weather Autonomous Drone" project was sponsored by Ultool, LLC to the KSU Research and Service Foundation to create a lightweight drone capable of capturing HD video during all-weather operations. The conditions of all-weather operation include rainfall of one inch per hour and wind speeds of up to twenty miles per hour. In addition, a global minimum structural safety factor of two is required to ensure the system's integrity in extreme weather conditions. Potential mission profiles include autonomous aerial delivery, topological mapping in high moisture areas, security surveillance, search and rescue operations, emergency transportation of medical supplies, and …
Quantification Of Various Types Of Biases In Large Language Models, Sudhashree Sayenju
Quantification Of Various Types Of Biases In Large Language Models, Sudhashree Sayenju
Doctor of Data Science and Analytics Dissertations
Natural Language Processing (NLP) systems are included everywhere on the internet from search engines, language translations to more advanced systems like voice assistant and customer service. Since humans are always on the receiving end of NLP technologies, it is very important to analyze whether or not the Large Language Models (LLMs) in use have bias and are therefore unfair. The majority of the research in NLP bias has focused on societal stereotype biases embedded in LLMs. However, our research focuses on all types of biases, namely model class level bias, stereotype bias and domain bias present in LLMs. Model class …
Ransomware: Evaluation Of Mitigation And Prevention Techniques, Juanjose Rodriguez-Cardenas
Ransomware: Evaluation Of Mitigation And Prevention Techniques, Juanjose Rodriguez-Cardenas
Symposium of Student Scholars
Ransomware is classified as one of the main types of malware and involves the design of exploitations of new vulnerabilities through a host. That allows for the intrusion of systems and encrypting of any information assets and data in order to demand a sum of payment normally through untraceable cryptocurrencies such as Monero for the decryption key. This rapid security threat has put governments and private enterprises on high alert and despite evolving technologies and more sophisticated encryption algorithms critical assets are being held for ransom and the results are detrimental, including the recent Colonial Pipeline ransomware attack in 2021 …
Security And Privacy Analysis Of Wearable Health Device, Abm Kamrul Islam Riad
Security And Privacy Analysis Of Wearable Health Device, Abm Kamrul Islam Riad
Symposium of Student Scholars
Wearable technology allows for consumers to record their healthcare data for either personal or clinical use via portable devices. As advancements in this technology continue to rise, the use of these devices has become more widespread. In this paper, we examine the significant security and privacy features of three health tracker devices: Fitbit, Jawbone and Google Glass. We also analyze the devices' strength and how the devices communicate via its Bluetooth pairing process with mobile devices. We explore possible malicious attacks through Bluetooth networking. The outcomes of this analysis illustrate how these devices allow third parties to access sensitive information, …
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) …
Towards A Development Of A Mobile Application Security Invasiveness Index, Sam Espana
Towards A Development Of A Mobile Application Security Invasiveness Index, Sam Espana
KSU Proceedings on Cybersecurity Education, Research and Practice
The economic impact of Mobile IP, the standard that allows IP sessions to be maintained even when switching between different cellular towers or networks, has been staggering in terms of both scale and acceleration (Doherty, 2016). As voice communications transition to all-digital, all-IP networks such as 4G, there will be an increase in risk due to vulnerabilities, malware, and hacks that exist for PC-based systems and applications (Harwood, 2011). According to Gostev (2006), in June, 2004, a well-known Spanish virus collector known as VirusBuster, emailed the first known mobile phone virus to Kaspersky Lab, Moscow. Targeting the Symbian OS, the …