SACM - United Kingdom
Permanent URI for this collectionhttps://drepo.sdl.edu.sa/handle/20.500.14154/9667
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Item Restricted Design, Development and Deployment of Customisable Mobile and IoT Systems to Enhance Mosquito Surveillance(University College London, 2025-04-10) Aldosery, Aisha; Kostkova, PattyMosquito-borne diseases pose significant public health challenges in tropical and subtropical regions, requiring precise and efficient surveillance methods. Traditional field data collection methods often lack the accuracy, timeliness and efficiency required to control outbreaks. This research advances mosquito field surveillance by designing, developing, and deploying two digital solutions customised for distinct environmental settings in Northeast Brazil and Madeira Island: a Mobile Surveillance System and an Internet of Things (IoT) Environmental Monitoring System. Developed through iterative processes and stakeholder engagement, these adaptable and scalable systems enhance the accuracy and granularity of data collection. The Mobile Surveillance System was adapted to regional requirements: in Brazil, it comprises a mobile app for field agents and a web platform for supervisors; in Madeira, it combines both functionalities into a single, unified mobile app. The implementation of both applications shares a common architecture that not only proves the systems’ generalisability but also boosts operational efficiency and data accuracy by digitising field data, supporting field agents, and aiding supervisors in managing activities. The IoT-based Environmental Monitoring System, featuring a five-layer architecture, including Arduino microcontrollers, weather and water sensors, and a water pump, autonomously and continuously captures high-resolution data, offering deeper insights into environmental influences on mosquito populations and supporting precise, location-specific predictive modelling. Detailed statistical analyses using Bayesian hierarchical models and correlation studies were conducted to pinpoint critical environmental predictors of mosquito breeding. Furthermore, a neural network classification-based predictive model was developed, enhancing weekly mosquito presence predictions by analysing temporal and sequential environmental patterns. This research distinguishes itself through its real-world deployments, addressing infrastructure, logistics, and technology challenges, while underscoring the importance of a process-oriented approach in tool development and recommending longitudinal deployments to assess the long-term impact of these technologies on mosquito population control and disease management in diverse environments.14 0Item Restricted Software-based Fault-Tolerant Internet of Things (IoT) Multi-Sensor Device using the BEAM Virtual Machine(Newcastle University, 2024-08-22) Alghamdi, Abdulrahman; Bystrov, AlexThe use of Internet of Things (IoT) devices in many industries, such as healthcare, agriculture, and transportation, has led to the reliability of such devices to become an essential requirement. It was argued that future business models would be dependent on IoT infrastructure. This project aimed to implement fault-tolerant IoT software using the Erlang virtual machine (BEAM) on the Raspberry Pi. The faults addressed are software faults, stuck-at-fault, and data loss faults. The objective was to build a multi-sensor IoT device that links the sensors to the cloud. It was decided to use the Elixir programming language as it had better support for external dependency and embedded systems. As for hardware, two sensors connected to the Raspberry Pi were used. A supervision tree was implemented using the Elixir language in Raspberry Pi, and experiments were then conducted to test the implementation. The implementation achieved a mean time to recovery (MTTR) of 2.16 milliseconds and 296 milliseconds in publish time. Moreover, it was found that increases in BEAM processes tend to be efficient in CPU usage due to a logarithmic relationship. The results proved BEAM as a substantial solution for IoT to meet digital business needs. The author is confident to recommend the BEAM as the tool for future reliable IoT devices.21 0Item Restricted Adaptive Resilience of Intelligent Distributed Applications in the Edge-Cloud Environment(Cardiff University, 2024-04) Almurshed, Osama; Rana, OmerThis thesis navigates the complexities of Internet of Things (IoT) application placement in hybrid fog-cloud environments to improve Quality of Service (QoS) in IoT applications. It investigates the optimal distribution of a Service Function Chain (SFC), the building blocks of an IoT application, across the fog-cloud infrastructure, taking into account the intricate nature of IoT and fog-cloud environments. The primary objectives are to define a platform architecture capable of operating IoT applications efficiently and to model the placement problem comprehensively. These objectives involve detailing the infrastructure's current state, execution requirements, and deployment goals to enable adaptive system management. The research proposes optimal placement methods for IoT applications, aiming to reduce execution time, enhance dependability, and minimise operation costs. It introduces an approach to effectively manage trade-offs through the measurement and analysis of QoS metrics and requires the implementation of specialised scheduling and placement strategies. These strategies employ concurrency to accelerate the planning process and reduce latency, underscoring the need for an algorithm that best corresponds to the specific requirements of the IoT application domain. The study's methodology begins with a comprehensive literature review in the area of IoT application deployment in hybrid fog-cloud environments. The insights gained inform the development of novel solutions that address the identified limitations, ensuring the proposal of robust and efficient solutions.22 0Item Restricted An information security model for an Internet of Things-enabled smart grid in the Saudi Energy Sector(University of Southampton, 2024-07-22) Akkad, Abeer; Rezazadeh, Reza; Wills, Gary; Hoang, SonThe evolution of an Internet of Things-enabled Smart grid affords better automation, communication, monitoring, and control of electricity consumption. It is now essential to supply and transmit the data required, to achieve better sensing, more accurate control, wider information communication and sharing, and more rational decision-making. However, the rapid growth in connected entities, accompanied by an increased demand for electricity, has resulted in several challenges to be addressed. One of these is protecting energy information exchange proactively before an incident occurs. It is argued that Smart Grid systems were designed without any regard for security, which is considered a serious omission, especially for data security, energy information exchange, and the privacy of both consumers and utility companies. This research is motivated by the gap identified in the requirements and controls for maintaining cybersecurity in the bi-directional data flow within the IoT-enabled Smart Grid. Through literature and industry standards, the initial stages of the research explore and identify the challenges and security requirements. Threat modelling analysis identified nine internet-based threats, proposing an initial information security model. This initial model is validated using expert reviews, resulting in a reference model that includes seven security requirements and 45 relevant security controls. To demonstrate the usefulness of this reference model as a foundation for further research, a segment of the reference model is elaborated using Event-B formal modelling. This approach assists in incorporating additional details during refinements and confirming the consistency of those details. The formal modelling process begins by formulating the functional requirements in a consistent model and then augmenting it with security controls. The effectiveness of these security controls is validated and verified using formal modelling tools. The contribution of this research, therefore, is the unique approach to developing a framework for an IoT-enabled Smart Grid (SG) by utilising threat analysis and expert reviews in combination with formal methods. As the field of security continues to evolve, this generic framework and formal template can be reused as a foundation for further analysis of other components or access points, and to implement new security controls. The resulting model enables field experts, security practitioners, and engineers to verify any changes made, ensuring they do not compromise the security of information flow within the IoT-enabled Smart Grid during the initial design stages of the system life cycle.47 0Item Restricted IAI-CGM: A Novel Theoretical Framework for Internet of Things -Enabled Continuous Glucose Monitoring Adoption for Self-Empowerment Perspectives Among Saudi Patients with Type 1 Diabetes(University of Sussex, 2024-07-11) Almansour, Hamad; Beloff, Natalia; White, MartinBackground: The alarming surge in the occurrence of diabetes in Saudi Arabia has been primarily linked to the adoption of a "westernised" lifestyle, especially in dietary practices. Despite the existence of treatment facilities, projections indicate that diabetes will affect approximately 25% of Saudi Arabia's adult population by 2030. Addressing this worrying situation regarding type 1 diabetes mellitus (T1DM) requires a paradigm shift in health control dynamics. The emphasis is moving from relying solely on doctors and physicians to placing greater responsibility in the hands of patients. This shift implies that patients should possess enhanced knowledge and the means for self-empowerment over their diet and nutrition to address their health-related issues. This is where smart technology assumes significance, empowering patients to adopt self-care management roles with Internet of Things (IoT)- enabled devices. However, it is imperative that use of IoT-enabled continuous glucose monitoring (IoT-CGM) be implemented at diabetes primary care centres in order for this practice to be normalized among all patients in Saudi Arabia. It is challenging to accurately assess the current rate of smart technology adoption by patients and IoT integration in the Saudi healthcare sector. Patients’ IoT-CGM adoption may be caused by numerous factors, such as practical, technological, and user behaviour factors. The study seeks to gauge the extent to which Saudi Arabian patients with diabetes are ready to embrace IoT-CGM for self- empowerment. Aims and Objectives: The research aims to assess the readiness and willingness of primary diabetes care patients in Saudi Arabia to wear CGM devices, thereby allowing self-empowerment. This research examines the literature that represents the challenges and concerns influencing the adoption of IoT-CGM, taking into account the experiences of T1DM patients in the environment of Saudi Arabia. The theoretical framework of the adoption of IoT-CGM is based on the technology acceptance model (TAM). Consequently, a theoretical framework is proposed as intention to adopt internet of things-enabled continuous glucose monitoring (IAI-CGM) to assess the willingness of Saudi Arabian T1DM patients for self- empowerment. Methods: The quantitative primary data were collected from 873 T1DM patients in Saudi Arabia, aged at least 18 years old. Primary data were analysed using the research IAI-CGM framework. Next, the validity and reliability of instrument were measured after checking data normality in SPSS and then the hypotheses were analysed using structural equation modelling (SEM) in AMOS. In the following step, qualitative data were collected through 15 comprehensive semi-structured interviews to capture the viewpoints of T1DM patients. A thematic analysis was performed to explore themes grounded on the theoretical IAI-CGM framework to identify the significance of practical, technological, and user behaviour factors that influence the adoption intention of T1DM patients. Results: The results consolidate the critical factors into the proposed IAI-CGM framework, identifying the main elements crucial for the framework in the context of T1DM patients in Saudi Arabia. The comprehensive theoretical IAI-CGM framework, based on the TAM, was applied and extended to comprehend the factors affecting the intention to adopt IoT-CGM in the context of Saudi Arabia. The results indicate the significance of practical, technological, and user behaviour factors, both quantitatively and qualitatively. Conclusion: This study investigated the critical factors found in the theoretical IAI-CGM framework, such as practical, technological, and user behaviour factors, in the environment of Saudi Arabia. The research findings give valuable information regarding the willingness of Saudi Arabian T1DM patients to adopt IoT-CGM, which necessitates its integration into the Saudi healthcare system.12 0Item Restricted Security Countermeasures for Topology and Flooding Attacks in Low Power and Lossy Networks(University of Bristol, 2023-10-06) Algahtani, Fahad Mohammed F; Oikonomou, GeorgeInternet of Things have become an integral part in many industries such as health- care, home automation, automobile, and agriculture. Many applications of IoT use networks of unattended micro battery-operated devices with limited compu- tational power and unreliable communication systems. Such networks are called Low-Power and Lossy Network (LLN) which is based on a stack of protocols de- signed to prolong the life of an application by conserving battery power and mem- ory usage. Most commonly used routing protocol is the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL). RPL suffers from vulnerabilities related to routing paths formation, network maintenance, and response to some of its control messages. Specifically, compro- mised nodes can advertise falsified routing information to form sub-optimised paths or trigger network reformations. Furthermore, they can flood a network with join- ing requests to trigger a massive number of replies. No standardised RPL solutions provide the security against such attacks. Moreover, existing literature works are mostly based on using monitoring architectures, public key infrastructure (PKI), or a blacklisting approach. Any monitoring devices must be physically secured and utilising only secure communications which is not easily scaleable. Using PKI in LLNs is still a challenge as certificates management is unsuitable for LLN devices. Blacklisting nodes using their advertise addresses is clearly vulnerable to identity spoofing. Moreover, attacks described in few sentences could miss details which transforms any discussion on impact analysis to be subject to interpretation. Therefore, the aim of this dissertation is to first implement attacks using a developed framework to launch multiple attacks simultaneously on different nodes during specified times. Second, to analyse the strategies of an adversary when launching the aforementioned attacks. Then, the impact of the instigated attacks in each strategy is analysed to establish a baseline for countermeasures evaluation. Finally, security countermeasures for the aforementioned attacks are proposed as well as their performances are evaluated. In countering the attack responsible for forming sub-optimised routing paths, preloading a minimum relative location in each node has filtered out any future attempts to accept false routing metrics. As for the attack causing unnecessary net- work reformations, nodes will only accept cryptographically authenticated routing information to trigger future network rebuilds. Lastly, any faster interarriving join- ing requests will be evaluated against thresholds with hysteresis to adjust RPL’s response to potential floods.30 0Item Restricted Profiling IoT Botnet Activity(University of Glasgow, 2024-02-09) Almazarqi, Hatem Aied; Marnerides, AngelosUndoubtedly, Internet of Things (IoT) devices have evolved into a necessity within our modern lifestyles. Nonetheless, IoT devices have proved to pose significant security risks due to their vulnerabilities and susceptibility to malware. Evidently, vulnerable IoT devices are enlisted by attackers to participate into Internet-wide botnets in order to instrument large-scale cyber-attacks and disrupt critical Internet services. Tracking these botnets is challenging due to their varying structural characteristics, and also due to the fact that malicious actors continuously adopt new evasion and propagation strategies. This thesis develops BotPro framework, a novel data-driven approach for profiling IoT botnet behaviour. BotPro provides a comprehensive approach for capturing and highlighting the behavioural properties of IoT botnets with respect to their structural and propagation properties across the global Internet. We implement the proposed framework using real-world data obtained from the measurement infrastructure that was designed in this thesis. Our measurement infrastructure gathers data from various sources, including globally distributed honeypots, regional Internet registries, global IP blacklists and routing topology. This diverse dataset forms a strong foundation for profiling IoT botnet activity, ensuring that our analysis accurately reflects behavioural patterns of botnets in real-world scenarios. BotPto encompasses diverse methods to profile IoT botnets, including information theory, statistical analysis, natural language processing, machine learning and graph theory. The framework's results provide insights related to the structural properties as well as the evolving scanning and propagation strategies of IoT botnets. It also provides evidence on concentrated botnet activities and determines the effectiveness of widely used IP blacklists on capturing their evolving behaviour. In addition, the insights reveal the strategy adopted by IoT botnets in expanding their network and increasing their level of resilience. The results provide a compilation of the most important autonomous system (AS) attributes that frequently embrace IoT botnet activity as well as provide a novel macroscopic view on the influence of AS-level relationships with respect to IoT botnet propagation. Furthermore, It provides insights into the structural properties of botnet loaders with respect to the distribution of malware binaries of various strains. The insights generated by BotPro are essential to equip next generation automated cyber threat intelligence, intrusion detection systems and anomaly detection mechanisms with enriched information regarding evolving scanning, establishment and propagation strategies of new botnet variants. Industry will be equipped with even more improved ways to defend against emerging threats in the domains of cyber warfare, cyber tourism and cyber crime. The BotPro framework provides a comprehensive platform for stakeholders, including cybersecurity researchers, security analysts and network administrators to gain deep and meaningful insights into the sophisticated activities and behaviour exhibited by IoT botnets.46 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.51 0Item Restricted Optimizing Task Allocation for Edge Compute Micro-Clusters(2023-07-24) Alhaizaey, Yousef; Singer, JeremyThere are over 30 billion devices at the network edge. This is largely driven by the unprecedented growth of the Internet-of-Things (IoT) and 5G technologies. These devices are being used in various applications and technologies, including but not limited to smart city systems, innovative agriculture management systems, and intelligent home systems. Deployment issues like networking and privacy problems dictate that computing should occur close to the data source at or near the network edge. Edge and fog computing are recent decentralised computing paradigms proposed to augment cloud services by extending computing and storage capabilities to the network's edge to enable executing computational workloads locally. The benefits can help to solve issues such as reducing the strain on networking backhaul, improving network latency and enhancing application responsiveness. Many edge and fog computing deployment solutions and infrastructures are being employed to deliver cloud resources and services at the edge of the network — for example, cloudless and mobile edge computing. This thesis focuses on edge micro-cluster platforms for edge computing. Edge computing micro-cluster platforms are small, compact, and decentralised groups of interconnected computing resources located close to the edge of a network. These micro-clusters can typically comprise a variety of heterogeneous but resource-constrained computing resources, such as small compute nodes like Single Board Computers (SBCs), storage devices, and networking equipment deployed in local area networks such as smart home management. The goal of edge computing micro-clusters is to bring computation and data storage closer to IoT devices and sensors to improve the performance and reliability of distributed systems. Resource management and workload allocation represent a substantial challenge for such resource-limited and heterogeneous micro-clusters because of diversity in system architecture. Therefore, task allocation and workload management are complex problems in such micro-clusters. This thesis investigates the feasibility of edge micro-cluster platforms for edge computation. Specifically, the thesis examines the performance of micro-clusters to execute IoT applications. Furthermore, the thesis involves the evaluation of various optimisation techniques for task allocation and workload management in edge compute micro-cluster platforms. This thesis involves the application of various optimisation techniques, including simple heuristics-based optimisations, mathematical-based optimisation and metaheuristic optimisation techniques, to optimise task allocation problems in reconfigurable edge computing micro-clusters. The implementation and performance evaluations take place in a configured edge realistic environment using a constructed micro-cluster system comprised of a group of heterogeneous computing nodes and utilising a set of edge-relevant applications benchmark. The research overall characterises and demonstrates a feasible use case for micro-cluster platforms for edge computing environments and provides insight into the performance of various task allocation optimisation techniques for such micro-cluster systems.13 0Item Restricted Towards Reliable Logging in the Internet of Things Networks(2022) Alhajaili, Sara; Jhumka, ArshadThe Internet of things is one of the most rapidly developing technologies, and its low cost and usability make it applicable to various critical disciplines. Being a component of such critical infrastructure needs, these networks have to be dependable and offer the best outcome. Keeping track of network events is one method for enhancing network reliability, as network event logging supports essential processes, such as debugging, checkpointing, auditing, root-cause analysis, and forensics. However, logging in the IoT networks is not a simple task. IoT devices are positioned in remote places with unstable connectivity and inadequate security protocols, making them vulnerable to environmental flaws and security breaches. This thesis investigates the problem of reliable logging in IoT networks. We concentrate on the problem in the presence of Byzantine behaviour and the integration of logging middleware into the network stack. To overcome these concerns, we propose a technique for distributed logging by distributing loggers around the network. We define the logger selection problem and the collection problem, and show that only the probabilistic weak variant can solve the problem. We examine the performance of the Collector algorithm in several MAC setups. We then explore the auditability notion in IoT; we show how safety specification can be enforced through the analogies of fair exchange. Next, we review our findings and their place in the existing body of knowledge. We also explore the limits we faced when investigating this problem, and we finish this thesis by providing opportunities for future work.9 0