Saudi Cultural Missions Theses & Dissertations
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Item Restricted Analysing Cybersecurity Risk Assessment Model for Healthcare Systems in Saudi Arabia(Saudi Digital Library, 2025-05) Alghamdi, Abdulmonem; Vasileios, AdamosThis study analyses the Saudi Arabian's cybersecurity issues in healthcare systems and assesses the usefulness of international risk assessment models in some frameworks such as ISO/IEC 27001 and NIST. It identifies major threats like ransomware, phishing, data breaches, and insider risks based on survey responses from medical professionals like medical staff, cybersecurity specialists and administrative managers. Variety of medical institutions members with difference in beds capability, number of branches and financial situation that guarantees the national-wide needs study. Findings point to critical weaknesses in the current models, especially their incompatibility with local regulations and organisational cultures and special needs. Consequently, the study emphasises the necessity of a tailored cybersecurity risk assessment model that is particular to the Saudi healthcare environment. The research highlights key elements and offers suggestions to improve cybersecurity resilience in accordance with national policies and Vision 2030 objectives, even though it does not fully implement a model.23 0Item Restricted Scalable Distributed Ledger Paradigms for Secure IoT-Driven Data Management in Smart Cities(Saudi Digital Library, 2025) Alruwaill, Musharraf; Mohanty, Saraju P; Kougianos, EliasBlockchain has become a cornerstone of trustworthy, decentralised information governance. Consensus protocols and cryptographic linkages guarantee data integrity, immutability, and verifiable provenance, eliminating reliance on a single trusted authority and mitigating data fragmentation. Within smart‑healthcare ecosystems, these capabilities enable the shift from siloed, centralised repositories to distributed, patient‑centric infrastructures. Because clinical data are highly sensitive and strictly regulated, robust assurances of integrity, confidentiality, and fine‑grained authorisation are essential. Integrating blockchain and smart contracts with technologies such as distributed off‑chain storage and the Internet of Medical Things (IoMT) creates a resilient, scalable, and interoperable foundation for next‑generation healthcare data management. This research introduces hChain, a four‑generation family of distributed‑ledger frameworks that progressively strengthen security, intelligence, and scalability in smart‑healthcare environments. hChain 1.0 lays the groundwork with a blockchain architecture that safeguards patient data, supports real‑time clinical telemetry, and enables seamless inter‑institutional exchange. Building on this foundation, hChain 2.0 integrates InterPlanetary File System (IPFS) storage and smart‑contract enforcement to deliver tamper‑proof, fine‑grained access control. hChain 3.0 embeds on‑chain deep‑learning analytics, providing proactive, automated decision support across the care continuum while preserving data integrity. Finally, hChain 4.0 introduces a highly scalable, permissioned ledger augmented by an Attribute‑Based Access Control (ABAC) layer, ensuring dynamic, context‑aware authorisation in complex organisational settings. The results demonstrate practical solutions for transforming data infrastructures from centralised to decentralised architectures, providing techniques that facilitate seamless integration with existing systems while enhancing blockchain scalability and privacy.52 0Item Restricted Usage of Cyber Security to Protect Women and Children(Saudi Digital Library, 2025) Alotibi, Bander; Al-Doghman, FirasDigital safety especially for women and children is crucial, and cybersecurity is a big part of that. Using feminist and intersectional perspectives, this research explores how Protection Motivation Theory (PMT) and Social Learning Theory (SLT) explain cybersecurity behaviors. Empirical findings suggest that women and children are disproportionately affected by harassment, doxing, and identity theft. The research further reveals knowledge holes in cybersecurity awareness, showing that younger people quickly adopt security measures but engage in high-risk behaviors, whereas older people emphasize safety but lag in technical implementation. Gender differences are also important, with women more concerned about cybersecurity but less confident in dealing with threats, and men more confident but more willing to take risks. The research emphasizes education, legal reforms, technological advancements, and community awareness programs to address these challenges. Future research should investigate AI-driven cybersecurity tools, inclusive security policies, and bridging the digital divide. To create a safer digital environment for women and children, collaboration between governments, tech companies, and advocacy groups is essential.18 0Item Restricted The Role of Artificial Intelligence in Strengthening Cyber Defense Mechanisms: Opportunities and Challenges(University of Bedfordshire, 2024) Alanazi, Mohammed; Garner, LeeThis study explores the role of Artificial Intelligence (AI) in strengthening cyber defense mechanisms, focusing on the opportunities and challenges it presents. In recent years, AI has shown potential in enhancing threat detection, response efficiency, and proactive cybersecurity measures. The study examines various AI applications in cyber defense, including machine learning for real-time threat identification and natural language processing for analyzing large-scale data patterns. While AI provides significant advantages in mitigating cyber threats, challenges such as model interpretability, ethical concerns, and vulnerability to adversarial attacks persist. The findings contribute to cybersecurity by highlighting both the promising capabilities and limitations of AI in this domain, suggesting future research directions to address these challenges.21 0Item Restricted Detecting Supply Chain Threats(Saudi Digital Library, 2025) Akash Aravindan Paul Rajan; Nor Iman Binti Abdul Rashid; Ayham Al-Kilani; Alexandru-Aurel Constantin; Ashley Doel; Dr Erisa Karafili; Marwan Mousa Altamimi; Dr Erisa KarafiliThis study investigates the detection of supply chain threats in open-source software by developing an innovative system that integrates scraping techniques and artificial intelligence (AI) for intent analysis. The project aims to address critical vulnerabilities by analysing git commit messages and corresponding code changes, ensuring enhanced transparency and security in the software supply chain. The proposed system comprises a GitHub scraper that retrieves structured data using GraphQL and REST APIs, over- coming API rate limitations for efficient data collection. The collected data is processed by an AI model, ”Baymax,” which employs large language models (LLMs) to evaluate the alignment between commit messages and code changes. The system is designed with scalability and modularity to accommodate repositories of varying sizes and com- plexities. The project was implemented using Agile Scrum methodologies, employing iterative development practices with tasks prioritised through the MoSCoW framework. Collaboration within the development team was structured through specialised roles, and progress was monitored via sprints, stand-ups, and retrospectives. The results indicate that the system effectively enhances the integrity of open-source software by identi- fying discrepancies indicative of potentially malicious changes. Future work includes expanding platform compatibility, improving system performance, and incorporating user feedback to improve accuracy. This research contributes to the growing field of software supply chain security, with implications for broader applications in software development and beyond.12 0Item Restricted PREDICTORS OF CYBERSECURITY KNOWLEDGE, ATTITUDE, AND BEHAVIOURS AMONG NURSES IN SAUDI ARABIA(Saudi Digital Library, 2025-05-21) Alanazi, Abdulhamid Khalifah; KHALIFAH, ANASAbstract Background: Cybersecurity is becoming increasingly critical in healthcare, as nurses frequently access sensitive patient data through electronic health records (EHRs) and other digital platforms. Despite this, gaps in nurses' knowledge, attitudes, and behaviors (KAB) regarding cybersecurity pose risks to data security, especially in Saudi Arabia, where healthcare digitization is expanding rapidly. Research in this area remains limited. Aim: The aim of this study is to explore the predictors of cybersecurity knowledge, attitudes, and behaviors among nurses in Saudi Arabia. Methodology: This cross-sectional, descriptive correlational study was conducted in three hospitals in northern Saudi Arabia: King Khalid Hospital, Prince Abdulaziz Bin Musaed Hospital, and Qurayyat General Hospital. A total of 190 nurses were selected using a convenient sampling method, and then they were surveyed using the Human Aspects of Information Security Questionnaire (HAIS-Q) to assess their cybersecurity knowledge, attitude, and behavior (KAB). Sociodemographic, work-related, and organizational variables were analyzed using multiple regression to identify significant predictors of cybersecurity KAB17 0Item Restricted Project Handover Document: AppAttack and PT-GUI – Trimester 3, 2024(Saudi Digital Library, 2025-04-16) Alzahrani, Abdulmajeed Hussain; Archbold, Benjamin; Turner, RyanThis document outlines the comprehensive handover for the AppAttack and PT-GUI projects completed during Trimester 3, 2024, at Deakin University under units SIT374/764 and SIT378/782. AppAttack focused on providing real-world penetration testing and secure code review services through structured sub-projects targeting multiple clients, including DataBytes AMS, Gopher Guardian, and the Hardhat Company Website. PT-GUI enhanced educational penetration testing by offering a graphical toolkit with 72 tools, 12 walkthroughs, and integrated ChatGPT support. Both projects included automation, tool development, vulnerability assessments, and integration with cybersecurity frameworks such as NIST CSF and Essential Eight. The document details team contributions, development methodologies, upskilling resources, architecture, deliverables, and a roadmap for future improvements23 0Item Restricted Trust and Adoption of AI-Powered Cybersecurity in Cloud Computing(Saudi Digital Library, 2025) Algarni, Moneer Mohammed; Baihe, MaThis research investigates the trust and adoption of AI-powered cybersecurity solutions in cloud computing environments. As organizations increasingly rely on cloud services, traditional security approaches fall short in addressing evolving cyber threats. AI-driven tools offer advanced threat detection, anomaly identification, and automated response capabilities. However, concerns about trust, transparency, technical complexity, and data privacy continue to hinder widespread adoption. This study employs a mixed-methods approach, combining surveys and case studies, to explore the key factors influencing trust in AI systems and the barriers to their implementation. The findings highlight the importance of explainable AI, third-party audits, and staff training in building confidence. The research concludes with practical recommendations to help organizations integrate AI into cloud security frameworks effectively.28 0Item Restricted Responsibility for Online Harms: A Critical Analysis of Cyber Governance in Saudi Arabia(Saudi Digital Library, 2025-03) Alsaiedi, Yara M; Basu, Subhajit; Walker, CliveThis thesis investigates the topic of internet governance within the context of Saudi Arabia. It focuses on the component of ‘Responsibility’ for internet governance when applied to the policy area of combating online harms. As such, the research work investigates and evaluates the present framework of responsibility devised to address online harms, considering the assemblage which regulates online content and cybersecurity in the Kingdom of Saudi Arabia. This approach aims to facilitate the prevention and mitigation of the harmful effects of online activities and content, thereby aligning with the objectives outlined in the Saudi state’s long-term project known as Vision 2030. The thesis adopts the hypothesis that effectively addressing online harms requires a primary objective of establishing a robust responsibility structure. This method can best be achieved by facilitating the active participation of all stakeholders in the strategic deployment of responsive – including preventive – measures. Consequently, the thesis advocates a multistakeholderism approach with reference to governance for the prevention and mitigation of online harms in Saudi Arabia. It evaluates the effectiveness and fairness of the responsibility structure in fostering cybersecurity and mitigating the harmful effects of online content in the Saudi context. The formal study employs semi-structured interviews with elite figures and authorities from governmental and private organisations, internet content and service providers, as well as corporate users, which are the small and medium enterprises (SME) as internet users. Additionally, it integrates the policy transfer methodology to draw insights from the experiences of the United Kingdom in the realm of internet governance. In sum, the thesis proposes areas of improvement to develop a comprehensive online harms governance framework in Saudi Arabia. Such amendments are expected to contribute to the recognition and realisation of the declared Vision 2030 goals related to internet governance in the Saudi realm.8 0Item Restricted IDENTIFYING AND MITIGATING ZERO-DAY VULNERABILITIES IN INDUSTRIAL CONTROL SYSTEMS(Saudi Digital Library, 2024-12-29) Alali, Yahya Abdullah; Shakir, Humood WasanThis dissertation addresses the critical issue of zero-day vulnerabilities within Industrial Control Systems (ICS), which govern essential infrastructure sectors such as energy, water, and manufacturing. As ICS environments integrate with Information Technology (IT) systems for enhanced operational efficiency, they become increasingly susceptible to cyber threats, including undetected zero-day exploits that can severely disrupt physical processes. This study focuses on identifying and mitigating zero-day vulnerabilities within ICS by developing a software tool that monitors and detects deviations in Windows services configuration against baseline configurations set by ICS vendors. The research involved designing a tool using PowerShell to gather, preprocess, and compare service data from Windows-based ICS systems, aiming to identify potential misconfigurations or unauthorized modifications that could signal a zero-day exploit. Through an experimental setup in a controlled ICS environment, the tool was evaluated for its efficiency in detecting deviations in service existence and start modes, key indicators of potential vulnerabilities. Results demonstrate the tool’s high accuracy in detecting configuration drifts, enabling proactive vulnerability management and reducing the ICS attack surface. The study underscores the importance of continuous monitoring, baseline configuration checks, and anomaly detection as proactive security measures for ICS environments. This research contributes significantly to ICS security, proposing a scalable solution for safeguarding critical infrastructure against evolving cyber threats.13 0