SACM - United Kingdom
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Item Restricted A blockchain-based Approach for Secure, Transparent and Accountable Distributed System Environment(Saudi Digital Library, 2025) ALSHARIDAH, Ahmad Abdulrahman; Jha, Devki NandanRecent advances in distributed systems have revolutionised numerous industries by enabling efficient resource sharing and enhanced system scalability. These systems play a critical role in domains such as cloud and edge computing by supporting various applications and services. However, despite their many benefits, distributed systems face inherent trustworthiness challenges, including security threats, limited transparency, and the presence of untrusted entities. These challenges might threaten system reliability and present significant barriers to the broader adoption of distributed technologies. This thesis addresses these challenges by investigating the role of blockchain technology in enhancing trust within distributed systems. It presents three frameworks that work together to improve security, accountability, transparency, and fairness, creating a more resilient and reliable decentralised computing environment. I would like also to take the opportunity and thank the the members of my examining committee, Professor Ali Sadiq and Dr. Vlad Gonzalez for the insightful comments and valuable inputs. The first contribution is a blockchain-based auditing mechanism for cloud resource management. This system securely records resource allocation decisions, performance data, and policy compliance on an immutable ledger. By making these records transparent and tamper-proof, the mechanism provides clear evidence of service provider behaviour. This gives cloud customers and stakeholders confidence that scaling operations are conducted fairly and adhere to agreed-upon rules. The second contribution is RewardChain, an incentive mechanism for federated learning that addresses the lack of trust in traditional FL setups. By integrating blockchain to record each participant’s actions, RewardChain offers transparent and verifiable accountability. Using approximations of the Shapley value, it accurately evaluates and rewards honest contributions while identifying and penalising malicious behaviour. This approach ensures fair compensation, promotes long-term collaboration, and ultimately enhances the quality of the jointly trained models. The third framework, SecureFed, addresses data poisoning attacks in federated learning. It combines cosine similarity metrics for anomaly detection with blockchain-based validation to thoroughly analyse suspicious model updates before incorporating them into the global model. This hybrid defence strategy significantly strengthens model robustness, reducing the risk of adversarial interference and enhancing trust in learning. Together, these three frameworks illustrate how blockchain can transform distributed systems by embedding transparency, fairness, and security into their core. By ensuring accountable cloud operations, reinforcing fair incentive structures, and safeguarding models against attacks, this research paves the way for distributed systems that are more trustworthy, equitable, and robust. Ultimately, it highlights the foundation for the continued evolution of secure and reliable decentralised computing ecosystems.15 0