SACM - United Kingdom
Permanent URI for this collectionhttps://drepo.sdl.edu.sa/handle/20.500.14154/9667
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Item Restricted Enhancing Trust Modelling for the Internet of Underwater Things(University of Nottingham, 2025) Almutairi, Abeer; Furnell, Steven; Carpent, XavierThe Internet of Underwater Things (IoUT) has gained growing interest from researchers and industry alike, due to its potential for advancing the development of smart cities and underwater intelligent systems. However, the harsh and unpredictable nature of underwater environments, coupled with the inherent limitations of existing technologies, presents significant challenges to establishing a sustainable IoUT. Furthermore, the open nature of such networks renders them highly susceptible to malicious attacks and security threats. Traditional security measures, which are widely implemented in conventional cyber systems, exhibit severe performance constraints in underwater networks, highlighting the urgent need for novel security solutions that meet the unique requirements of underwater networks. Trust modelling has been widely recognised as an effective soft security measure to mitigate the impact of internal attacks. It primarily achieves this by analysing behavioural characteristics between network entities, thereby introducing a layer of defence against malicious activities. In the context of underwater networks, trust establishment between nodes has the potential to significantly enhance overall network security. However, existing Trust Modelling and Management (TMM) often fail to address the complexities of underwater environments, which necessitate new TMM that are lightweight, accurate, and decentralised. In light of these limitations, this thesis investigates and enhances TMM to meet the application requirements of underwater networks while addressing the specific challenges inherent to IoUT. The central research question addressed in this thesis is: To what extent can existing TMM accommodate diverse network topologies within the IoUT and effectively mitigate potential attacks from both the communication and physical domains. In order to answer this question, a comprehensive understanding of the key challenges and potential application requirements for underwater networks is required. To facilitate this investigation, a simulated environment is constructed to analyse the effectiveness of TMM. This study critically evaluates the capabilities of current TMM in detecting malicious activities across various underwater network structures, identifying vulnerabilities, and exposing potential attack vectors. In response to these findings, this thesis proposes a distributed multi-dimensional TMM, referred to as the Mobility-Aware Trust Model (MATMU), designed to enhance the detection of malicious behaviour within the constraints of underwater environments. MATMU expands the metric domain to include mobility-aware metrics, allowing for the assessment of similarities and differences in node movement patterns. Additionally, the model employs a dynamic weighting strategy that integrates metrics from both the communication and physical domains. The performance of MATMU is evaluated through extensive simulations conducted across various underwater scenarios and attack models. The results demonstrate that MATMU effectively mitigates malicious behaviour, exhibiting notable improvements over benchmark models, particularly in terms of faster convergence and enhanced attack detection. These findings underscore the suitability of MATMU for strengthening secure and reliable communication in underwater networks. This thesis also tackles the critical issue of dishonest recommendations within TMM in the IoUT context, which is introduced by malicious entities, aiming to manipulate trust computations by providing false or misleading recommendations, thereby degrading the reliability and stability of the TMM. A novel recommendation evaluation method is introduced, combining filtering and weighting strategies to more effectively detect dishonest recommendations. The proposed model incorporates an outlier detection-based filtering technique and deviation analysis to evaluate recommendations based on both collective outcomes and individual experiences. Furthermore, a belief function is employed to refine recommendations by assigning weights based on criteria such as freshness, similarity, trustworthiness, and trust decay over time. This multi-dimensional approach demonstrates a marked improvement in recommendation evaluation, effectively capturing deceptive behaviours that exploit the complexities of IoUT. The effectiveness of the model is validated through extensive simulations and comparative analyses with existing trust evaluation methods, demonstrating consistently high performance across varying proportions of dishonest recommendations, with the highest accuracy improvement observed when dishonest recommendations constitute up to 45% of the total recommendations. These findings underscore the model’s potential to significantly enhance the reliability and security of IoUT networks.24 0Item Restricted Measuring Human’s Trust in Robots in Real-time During Human-Robot Interaction(Swansea University, 2025) Alzahrani, Abdullah Saad; Muneeb, Imtiaz AhmadThis thesis presents a novel, holistic framework for understanding, measuring, and optimising human trust in robots, integrating cultural factors, mathematical modelling, physiological indicators, and behavioural analysis to establish foundational methodologies for trust-aware robotic systems. Through this comprehensive approach, we address the critical challenge of trust calibration in human-robot interaction (HRI) across diverse contexts. Trust is essential for effective HRI, impacting user acceptance, safety, and overall task performance in both collaborative and competitive settings. This thesis investigated a multi-faceted approach to understanding, modelling, and optimising human trust in robots across various HRI contexts. First, we explored cultural and contextual differences in trust, conducting cross-cultural studies in Saudi Arabia and the United Kingdom. Findings showed that trust factors such as controllability, usability, and risk perception vary significantly across cultures and HRI scenarios, highlighting the need for flexible, adaptive trust models that can accommodate these dynamics. Building on these cultural insights as a critical dimension of our holistic trust framework, we developed a mathematical model that emulates the layered framework of trust (initial, situational, and learned) to estimate trust in real-time. Experimental validation through repeated interactions demonstrated the model's ability to dynamically calibrate trust with both trust perception scores (TPS) and interaction sessions serving as significant predictors. This model showed promise for adaptive HRI systems capable of responding to evolving trust states. To further enhance our comprehensive trust measurement approach, this thesis explored physiological behaviours (PBs) as objective indicators. By using electrodermal activity (EDA), blood volume pulse (BVP), heart rate (HR), skin temperature (SKT), eye blinking rate (BR), and blinking duration (BD), we showed that specific PBs (HR, SKT) vary between trust and distrust states and can effectively predict trust levels in real-time. Extending this approach, we compared PB data across competitive and collaborative contexts and employed incremental transfer learning to improve predictive accuracy across different interaction settings. Recognising the potential of less intrusive trust indicators, we also examined vocal and non-vocal cues—such as pitch, speech rate, facial expressions, and blend shapes—as complementary measures of trust. Results indicated that these cues can reliably assess current trust states in real-time and predict trust development in subsequent interactions, with trust-related behaviours evolving over time in repeated HRI sessions. Our comprehensive analysis demonstrated that integrating these expressive behaviours provides quantifiable measurements for capturing trust, establishing them as reliable metrics within real-time assessment frameworks. As the final component of our integrated trust framework, this thesis explored reinforcement learning (RL) for trust optimisation in simulated environments. Integrating our trust model into an RL framework, we demonstrated that dynamically calibrated trust can enhance task performance and reduce the risks of both under and over-reliance on robotic systems. Together, these multifaceted contributions advance a holistic understanding of trust measurement and calibration in HRI, encompassing cultural insights, mathematical modelling, physiological and expressive behaviour analysis, and adaptive control. This integrated approach establishes foundational methodologies for developing trust-aware robots capable of enhancing collaborative outcomes and fostering sustained user trust in real-world applications. The framework presented in this thesis represents a significant advancement in creating robotic systems that can dynamically adapt to human trust states across diverse contexts and interaction scenarios.18 0Item Restricted ACCEPTANCE OF BLOCKCHAIN TECHNOLOGY BY HIGHER EDUCATION INSTITUTIONS IN THE KINGDOM OF SAUDI ARABIA(Aston University, 2025) Alhumayzi, Mohammed; Batista, Luciano; Benson, VladlenaThe increasing adoption of new technologies in the Higher Education Institutions (HEIs) sector highlights the importance of exploring blockchain acceptance among employees. Adopting blockchain, as an emerging technology, is likely to encounter resistance among employees. This study explores this issue. Specifically, this study aims to determine the drivers and hindrances of blockchain acceptance among employees in the HEIs industry. To address this aim, this study proposes a framework that extends the unified theory of acceptance and use of technology (UTAUT) with individual characteristics. The framework represents factors that explain blockchain acceptance. The identified elements are performance expectancy (PE), effort expectancy (EX), social influence (SI), facilitating conditions (FC), trust, perceived security (SEC) and awareness (AW). The relationships among these factors were examined based on a quantitative approach, where an online questionnaire was employed to collect data from administrative and academic staff working for HEIs in the Kingdom of Saudi Arabia (KSA). Partial Least Squares Structural Equation Model (PLS-SEM) and Multi-group Analysis (MGA) techniques were employed to analyse 394 responses. The findings of this study revealed the direct drivers and hindrances of blockchain acceptance, i.e., PE, FC, SEC and AW. Additionally, this study demonstrated the moderating effects of AW between FC and blockchain acceptance. Furthermore, it determined specific indirect effects of the EX, trust and SEC on blockchain acceptance. Moreover, this research detected significant differences between categories’ subsamples and identified the significant factors of blockchain acceptance per subsample. Finally, this research identified where blockchain needs to be adopted most within the HEIs, i.e., financial exchange, certificate management, and students’ assessment areas. The HEIs industry in KSA could use these findings to develop concise strategies that encourage the adoption of blockchain. Scholars might also employ the proposed framework to investigate the adoption of blockchain.32 0Item Restricted Factors driving Mobile Shopping Apps Loyalty in the UK(University of East Anglia, 2024-08-22) Alkhairallah, Khulud; Alotaibi, DalalThe widespread adoption of digital technologies has substantially transformed many aspects of daily life, especially retail and consumer behaviour. A significant increase in online shopping through mobile applications is anticipated in the UK due to the growing popularity of smartphones, a trend known as mobile shopping (M-shopping) or mobile commerce (M-commerce). This dissertation investigates the factors influencing customer loyalty in M-shopping apps, an area that has not been extensively explored in existing literature. This study, which focuses on the UK market, looks at how user loyalty in mobile shopping applications is affected by four factors namely service quality, perceived usefulness, perceived ease of use, and trust. A questionnaire survey was conducted and 201 valid responses were received. Partial Least Squares Structural Equation Modelling (PLS-SEM) was used to analyse data and to test the research hypotheses. The analysis revealed that all four factors have significant direct influence on M-Shopping loyalty and they account for 61.1% of the variation in mobile shopping loyalty in the UK. The study offers practical insights for companies looking to increase customer loyalty in the ever-changing digital marketplace. It pinpoints strategies for improving these factors. The findings also advance our knowledge of how changing digital interactions and customer expectations affect loyalty in mobile shopping.26 0Item Restricted Extending the Technology Acceptance Model: Exploring Trust and Perceived Risk in the Adoption of Virtual Assistants within the Context of Saudi Arabia(Nottingham University, 2023-12-13) Altamimi, Bashaer; Muaid, ReemThis research examined, in depth, the factors that impact users' willingness to utilise virtual assistant apps in the Kingdom of Saudi Arabia. The analysis included trust and perceived risk as essential elements, expanding on the technology acceptance model. Drawing from the perspectives of 281 virtual assistant application users in Saudi Arabia, the results of the study confirmed and underscored the significant, positive roles played by both the technology acceptance model and user confidence in shaping users’ propensity to embrace virtual assistant applications. In addition, the study revealed that different dimensions of perceived risk, spanning performance, as well as psychological risks, privacy risks and security risks did not exert any noteworthy influence on the adoption of virtual assistant applications. These findings provide valuable strategic insights for virtual assistant companies, aiding them in devising strategies to attract users and efficiently allocating resources for customer growth and retention. Furthermore, this investigation presents empirical evidence that enhances the theoretical comprehension of users' intents to embrace virtual assistant apps, specifically in the context of Saudi Arabia.21 0Item Restricted Evaluation of the Effectiveness of Media Policy in Protecting Social Media Users in Saudi Arabia from Hate Speech and Discriminatory Content: Transparency, Awareness, Trust, and Future Vision(Saudi Digital Library, 2023-08) Alghannam, Hussain Ali; Boyle, RaymondThis groundbreaking study delves into the effectiveness of media policies in Saudi Arabia in combating hate speech and discriminatory content on social media platforms. Through a comprehensive exploration of Saudi users' perspectives, this research measures exposure levels, evaluates awareness and trust in state-enacted policies, and gauges users' optimism for future developments. The integration of quantitative and qualitative methods provides a nuanced understanding of the data. Results indicate relatively low exposure to harmful content, with 66.48% reporting no encounter, yet 33.52% experienced such content. Qualitative insights reveal a consensus on defining hate speech, aligning with global perspectives. Awareness of policies is high but calls for intensified education emerged, emphasising the correlation between awareness and trust. Remarkably, 88.26% express confidence in Saudi media policies. Optimism about future policy development is widespread, with over 90% expressing positivity. Recommendations for future research include broader inclusion of stakeholders, comparative studies with other cultures, and exploring the dynamics of trust and awareness. This study contributes to media management research, emphasising the importance of effective policies in creating respectful and protective digital spaces. Despite its Saudi focus, the study's implications transcend borders, advocating for global collaboration in mitigating harmful online content.110 0Item Restricted Explore The Perspective of the Public Institution Toward Their Collaboration with the Social Media Celebrities(Saudi Digital Library, 2023-08-10) Alreshwde, Bander; Patel, SusmiThe research’s central idea has been to explore and analyse the views and decisions of public authorities regarding their cooperative working with social-media influencers or celebrities. Methodology: The research integrated semi-structured interviews with 6 editors-in-chief and directors from Saudi media agencies. Thematic analysis was rigorously performed to evaluate the data findings.16 0Item Restricted An Exploration of The Use of Social Media (Websites/ Twitter) As A Public Relations Communication Technique by Saudi Charities for Relationship Building(2023) Aljaafar, Alhanouf; Rydzewska, Joanna; Rees, SianThis exploratory thesis is one of the first to investigate how charitable organisations in the Kingdom of Saudi Arabia (KSA) create dialogue, develop trust, and build relationships using websites and Twitter, aiming to identify strategic communication plans for enhancing fundraising through donor relationship-building via digital means. The theoretical framework comprises Social Exchange Theory, Kent and Taylor’s (1998) principles of dialogic communication, and the two-way symmetrical model of public relations (PR) to examine the use of websites and Twitter as PR tools. Data was collected through qualitative content analysis of the websites of 95 charities, 289 tweets from the Twitter accounts of seven charities, and face-to-face semi-structured interviews with 11 PR practitioners from five charities. The findings revealed that Saudi charities tended to use their websites as a source of information but underutilised the ability to facilitate dialogic communication with stakeholders. Usefulness of Information was the main dialogical principle of communication emerging from the website and Twitter analysis. However, the information disclosed on websites was insufficient, with 38 providing annual reports, 49 with media centres and 76 publishing financial reports. The findings showed that Saudi charitable organisations were not fully exploiting interaction and two-way communication on their websites or Twitter. A charity’s transparency and credibility influence potential donors to make contributions, and the interview results indicated that confidence can be built by delivering and promoting successes and providing visual images and financial reports, as these increase donations. This study offers insight into how Saudi charities use websites and Twitter to communicate and build trust with the key public, extending upon existing knowledge of how websites and social media can be used for PR purposes by charitable organisations. It concludes with implications of how Saudi charities can use websites and Twitter to build and maintain mutually beneficial relationships with stakeholders.27 0