SACM - United Kingdom
Permanent URI for this collectionhttps://drepo.sdl.edu.sa/handle/20.500.14154/9667
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Item Restricted Interactive Privacy Management for Internet of Things(Saudi Digital Library, 2025) Almuhander, Bayan; Perera, CharithThe balance between protecting user privacy while providing cost-effective devices that are functional and usable is a key challenge in the burgeoning Internet of Things (IoT). In traditional desktop and mobile, the primary interface is a screen; however, in IoT, screens are rare or small, invalidating many existing approaches to protecting user privacy. Users increasingly bring IoT devices into their environments without understanding how their data is gathered, processed, and used. Furthermore, users encounter various complexities in configuring their privacy settings, including a lack of transparency and difficulty locating the settings. Privacy visualisations are a common approach for assisting users in understanding the privacy implications. This thesis delves into providing usable privacy approaches to protect user privacy when using IoT. It explores novel approaches to address this balance, with an emphasis on privacy visualisation and user-friendly interfaces. This thesis provides three contributions. First, by scrutinising existing approaches to privacy visualisation across web, mobile, and IoT, we identified a challenge in privacy management (awareness and control) in the IoT domain. Building upon this, second, we established a link between privacy and data physicalisation. Accordingly, we proposed PrivacyCube, a novel data physicalisation designed to elevate privacy awareness within smart homes. Third, we explored privacy and tangible interfaces, from which we introduced PriviFy (Privacy Simplify-er). PriviFy is a novel user-friendly tangible interface aimed at simplifying the control of smart devices’ privacy settings. Through a series of studies, we validate PrivacyCube and PriviFy. PrivacyCube emerges as a valuable tool for enhancing privacy awareness. PriviFy demonstrates great potential in addressing the challenges associated with privacy configuration. Overall, the experimental results demonstrated in this thesis confirm our hypothesis that data physicalisation and tangi- ble interface improved privacy management in IoT by enhancing users’ privacy awareness and control.7 0Item Restricted “Exploring the Macroeconomic Implications of CBDCs”(Brunel University, 2024-09-05) Alnughaymishi, Saleh Mohammed; Korotana, MohammedThis dissertation examines the potential macroeconomic implications of CBDC adoption, focusing on monetary policy, financial stability, and economic growth. A comprehensive literature review explores the historical evolution of money and digital currencies, analysing various CBDC models and design choices. The study delves into the potential impacts of CBDCs on monetary policy transmission mechanisms and financial stability, while also considering the technological and operational challenges associated with their implementation. The dissertation provides a detailed analysis of the UK's legislative framework concerning CBDCs, including an overview of current financial legislation, proposed regulatory changes, and the role of the Bank of England. Comparative analyses with other jurisdictions offer a broader perspective on global regulatory approaches. Empirical analysis1 and case studies of CBDC implementations provide practical insights into the real-world implications of these digital currencies. Based on these findings, the dissertation presents policy recommendations for central banks, governments, financial institutions2, and technology providers to effectively navigate the challenges and opportunities presented by CBDCs.39 0Item Restricted A Study of Perspectives of Patients and Stakeholders regarding the Privacy, Security, and Confidentiality of Data collected via mHealth apps in Saudi Arabia: A Mixed Method Analysis(University of Warwick, 2024) Alhammad, Nasser; Epiphaniou, Gregory, Alajlani Mohannad and Arvanitis TheodorosMobile health (mHealth) apps have the potential to enhance healthcare service delivery but the adoption could be shaped by users’ awareness and concerns regarding patients’ data privacy, and security. This thesis aims to achieve the following research objectives; (1) to systematically assess patients’ perspectives and awareness level of data privacy, confidentiality, and security of mHealth apps, (2) to explore patients, healthcare workers and stakeholders’ perspectives regarding these issues, (3) to develop a model for predicting the influencing factors by combining the Technology Acceptance Model (TAM) and the PSC concept, and (4) propose initiatives to enhance the adoption of mHealth apps among patients. The research objectives were executed by systematically analysing 33 relevant articles on the research problems using a mixed-method study design comprising quantitative and qualitative phases. A cross-sectional survey instrument was piloted, validated and administered online to patients and end users (n = 600) of mHealth apps from various provinces in Saudi Arabia. Data were analysed using descriptive statistics and linear regression models. With a response rate of 90% (n = 567/600), most patients were aware about mHealth apps but moderate to high level of concerns were raised regarding data privacy and security. These concerns were significantly higher among female patients, those with higher educational qualifications, and younger age groups. Qualitative exploration among 25 stakeholders of mHealth apps revealed that patients needed to be more informed regarding data privacy and security than healthcare workers. Facilitators of mHealth apps include patient education, advanced security features, user-friendly features, online consultation for emergencies, remote monitoring features, and considering patients’ needs. In conclusion, patients’ socio-demographic factors and data security and privacy concerns influence their behavioural intention to use mHealth apps. Educating users on these issues, as well as targeting the younger population, may also be considered. The present findings will contribute to policymaking by informing the development of data security standards in mHealth apps, addressing user concerns, and enhancing adoption. It offers insights into socio-demographic factors influencing behavioural intention, guiding targeted awareness campaigns and educational initiatives. Additionally, the findings support the creation of user-centric features and advanced security measures, aligning with the goals of Vision 2030. This ensures that policymakers can implement evidence-based strategies to improve patient trust and the effective integration of mHealth technologies into Saudi Arabia’s healthcare system.51 0Item Restricted Adapting Homes in Saudi Arabia to Accommodate International Tourists: A Socio-cultural Design Study in Riyadh(The University of Sheffield, 2024) Almusaylihi, Eman; Lanuza, Felipe.16 0Item Restricted IoT: current challenges and future applications(Saudi Digital Library, 2023-08-30) Almutairi, Nader; Palego, CristianoThis master's thesis explores the dynamic landscape of Internet of Things (IoT) technology, focusing on its transformative potential and obstacles. The study explores the role of IoT devices in reshaping industries, enhancing efficiency, and enhancing resource management by navigating the complex web of IoT devices. The investigation identifies key contributors to the prevalent security vulnerabilities in IoT systems and suggests strategies to strengthen their defences. The research creates a comprehensive framework that combines encryption, authentication, and anomaly detection mechanisms to address the pressing need for secure and efficient IoT solutions. Utilising cutting-edge technologies such as machine learning and blockchain, the framework not only improves the security of IoT devices, but also guarantees data integrity and user privacy. This solution's significance rests in its capacity to pave the way for safer and more reliable IoT technology, thereby nurturing confidence among users, industries, and policymakers. The results of the study demonstrate the effectiveness of the proposed framework in protecting IoT ecosystems from cyber threats, while also addressing ethical and regulatory concerns. Beyond technology, this research has implications for societal well-being, sustainable practises, and economic growth. By mitigating the security risks associated with the Internet of Things, this study establishes the foundation for realising the maximum potential of IoT technology in various industries.61 0Item Restricted Developing an Efficient and Privacy-Preserving Energy Theft Detection System for Smart Grids(Saudi Digital Library, 2023-09-25) Alromih, Arwa; Clark, John; Gope, ProsantaEnergy plays an essential role in our lives. Merging the existing electricity networks with distributed energy resources and information and communications technology (ICT) changes how companies and customers generate, distribute, and consume energy. This integration transforms the legacy electricity networks into smart systems, or what is currently known as the Smart Grid (SG). Smart grid infrastructure has been one of the major industrial revolutions that has attracted widespread adoption across the globe. Therefore, they can be the target of major security risks as they are not inherently secure. In this sector, sensors’ and meters’ data are the main factors in any decision-making process. This introduces the need to develop appropriate security mechanisms that ensure data integrity. One of the main attacks against data integrity in energy networks is energy theft. This attack can be made by injecting false consumption data into the network. The consequences of a successful energy theft attack on smart grid systems can be severe and far-reaching as it can result in power outages and physical damage to equipment which can be a safety hazard to individuals. Therefore, secure techniques are needed to detect any anomalies or injection attempts and smart meter data integrity should be considered and ensured. In this thesis, we propose three machine learning (ML) based energy theft detectors that address the existing challenges facing current research in this domain. In particular, we consider the impact proposed by prosumers in launching new types of energy thefts and how to detect them. We also show how to fully utilise data from multiple sources for better detection performance. To decrease the probability of any privacy breaches caused by the use of customers’ data, privacy-preserving approaches are proposed. Lastly, we tackle the significant impact on demand management caused by energy thefts by proposing a combined energy theft detector with demand management. The findings presented in this thesis show that our approaches can accurately detect energy thefts, with minimal information leakage. Moreover, the results are also promising in providing a clear link between reliably managing demand when energy theft is considered.28 0Item Restricted Secure Data-Sharing Among Healthcare Organisations in Saudi Arabia(Saudi Digital Library, 2023-07-17) Alzahrani, Ahmed; Wills, GaryThe healthcare sector is suffering from the inefficiencies in handling its data. Many patients and healthcare organisations are frustrated by the numerous hurdles to obtaining current real-time patient information that are leading to delays in treatment. The healthcare sector’s attention has been drawn to blockchain technology for a part of the solution, especially after this technology was successfully applied in the financial sector to improve the security of transactions. The lack of data-sharing in the healthcare sector is considered a significant issue worldwide. This research focuses on the gap by investigating the benefits of using blockchain at the Ministry of Health in Saudi Arabia. The study achieves this by providing a detailed analysis of the healthcare sector and evaluating how blockchain technology improves data-sharing in a more secure way. This research proposes a framework that identifies the factors that will provide data-sharing among healthcare organisations using blockchain. The framework has three categories: healthcare systems factors; security factors; and blockchain factors. These were identified by critically reviewing published studies together with factors from the relevant industrial standards within the context of the Kingdom of Saudi Arabia (KSA). A triangulation technique was used to achieve reliable results in three steps: a literature review; expert review; and questionnaires. This provided a comprehensive picture of the research topic, validating and confirming the results. To construct the framework the factors of the framework were comprehensively studied and extracted from the literature, then analysed, cleared of duplicates and categorised. Once the framework had been developed, to review and confirm it a study was carried out with healthcare IT specialists and blockchain experts. The expert review findings confirmed that all the proposed factors were important, and suggested recategorising one factor and removing another. After revising the proposed framework according to the expert review and recommendations, a questionnaire was distributed to healthcare IT specialists and blockchain experts in various organisations. Its results were analysed via a one-sample t-test and its data integrity analysed using Cronbach’s alpha, showing that all the factors are statistically significant. The confirmed framework has been based on literature and expert reviews and is supported by a practitioner survey. The framework can be used to inform decision-makers and the Ministry of Health about the factors that will provide data-sharing among healthcare organisations using blockchain. A new instrument was developed. A total of 238 IT and blockchain experts in Saudi healthcare organisations used the instrument. It was developed using the framework to identify the factors that will provide data-sharing among healthcare organisations. The instrument was evaluated using two tests that examined the internal reliability and the validity tests. The results from the instrument were used to develop a model using Structural Equation Modelling (SEM). The resulting data clearly showed a good fit of the structural model and measurement analyses. The key outcomes of the validation study revealed that the factors were discovered to have a direct and statistically significant effect on the model. This specifies that the proposed model fits the data and applies to the KSA context. The contributions of this research are as follows: first, it developed a framework within the KSA context and, second, from the framework a data-sharing instrument was developed, the results of which were used to generate a structural equation model. Overall, the outcomes of this study are valuable information in terms of recommendations to experts and healthcare organisations. Simply put, these findings can assist data sharing and encourage the spread of this phenomenon across countries in the Middle East, particularly in Saudi Arabia.67 0