Date of Defense
8-11-2024 10:30 AM
Location
E1-1027
Document Type
Thesis Defense
Degree Name
Master of Science in Information Security
College
College of Information Technology
Department
Information Security
First Advisor
Dr. Khaled Shuaib
Keywords
Digital twin, Data quality, Data security, Internet Of Things, Probability-Impact (P-I) matrix, Risk Priority Number (RPN), Blockchain
Abstract
This thesis is concerned with the data quality and security of the digital twin and how it is going to impact its adoption, trustworthiness, and potential for real-world applications. By addressing the potential vulnerabilities and ensuring the integrity of data, this research aims to contribute to the development of robust and trustworthy digital twin standards and policies that is going to complement the existing international standards across different domains. Moreover, it underscores the important need to establish robust standards to ensure the successful and secure deployment of digital twins across industries. Previous research, while valuable, may not have fully addressed the critical interplay between data quality and security within the digital twin environment. To address this gap, a survey was distributed to digital twin users and experts. To thoroughly analyze the survey results and assess the true effectiveness of digital twin technology, we will employ some analytical procedures, utilizing robust tools such as ATLAS.ti and qualitative matrices such as the Probability-Impact (P-I) matrix and Risk Priority Number (RPN). The result of this paper is addressing valuable data quality and security standards for the digital twin, which is going to address the risks analyzed from the case studies to mitigate identified vulnerabilities, enhance data integrity, and ensure that the digital twin system is resilient against potential threats. The survey and case study analysis yield a comprehensive understanding of these critical risks to address the importance of these aspects of the digital twin.
Included in
DEVELOPING A FRAMEWORK FOR DIGITAL TWIN DATA QUALITY AND SECURITY CONTROLS
E1-1027
This thesis is concerned with the data quality and security of the digital twin and how it is going to impact its adoption, trustworthiness, and potential for real-world applications. By addressing the potential vulnerabilities and ensuring the integrity of data, this research aims to contribute to the development of robust and trustworthy digital twin standards and policies that is going to complement the existing international standards across different domains. Moreover, it underscores the important need to establish robust standards to ensure the successful and secure deployment of digital twins across industries. Previous research, while valuable, may not have fully addressed the critical interplay between data quality and security within the digital twin environment. To address this gap, a survey was distributed to digital twin users and experts. To thoroughly analyze the survey results and assess the true effectiveness of digital twin technology, we will employ some analytical procedures, utilizing robust tools such as ATLAS.ti and qualitative matrices such as the Probability-Impact (P-I) matrix and Risk Priority Number (RPN). The result of this paper is addressing valuable data quality and security standards for the digital twin, which is going to address the risks analyzed from the case studies to mitigate identified vulnerabilities, enhance data integrity, and ensure that the digital twin system is resilient against potential threats. The survey and case study analysis yield a comprehensive understanding of these critical risks to address the importance of these aspects of the digital twin.