SACM - United States of America
Permanent URI for this collectionhttps://drepo.sdl.edu.sa/handle/20.500.14154/9668
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Item Restricted Leveraging Blockchain for Trust Enhancement in Decentralized Marketplaces: A Reputation System Perspective(Old Dominion University, 2024-07) Aljohani, Meshari; Olariu, Stephan; Mukkamala, RaviCentralized marketplaces provide reliable reputation services through a central authority, but this raises concerns about single points of failure, user privacy, and data security. Decentralized marketplaces have emerged to address these issues by enhancing user privacy and transparency and eliminating single points of failure. However, decentralized marketplaces face the challenge of maintaining user trust without a centralized authority. Current blockchain-based marketplaces rely on subjective buyer feedback. Additionally, the transparency in these systems can deter honest reviews due to fear of seller retaliation. To address these issues, we propose a trust and reputation system using blockchain and smart contracts. Our system replaces unreliable buyer feedback with objective transaction assessments. Performance challenges of blockchain-based systems are tackled through three innovative schemes, resulting in a substantial improvement over the baseline approach. Furthermore, we proposed a decentralized marketplace utilizing blockchain-based smart contracts to address privacy concerns in buyer reviews that arise from the transparency of decentralized marketplaces. This enables buyers to use one-time identities for reviews to promote anonymity. This system ensures that buyers provide reviews by requiring a review fee, which is fully refunded after the review is submitted. Moreover, we proposed a trust and reputation service based on Laplace’s Law of Succession, where trust in a seller is defined as the subjective probability that they will fulfill their contractual obligations in the next transaction. This method accommodates multi-segment marketplaces and time-varying seller performance, predicts trust and reputation far into the future, and discounts older reputation scores. In addition, we propose SmartReview, an automated review system utilizing blockchain smart contracts to generate objective, bias-free reviews. The review module is designed as a smart contract that takes the contract terms and the evidence provided by the buyer and seller as inputs. It employs advanced computer vision and machine learning techniques to produce quantitative and qualitative reviews for each transaction, ensuring objectivity and eliminating reviewer bias. Lastly, we introduce a structured blockchain architecture featuring a layered approach. This architecture includes mechanisms for secure transaction recording and efficient query retrieval through auxiliary indexing, demonstrating significant advancements in decentralized data management.28 0Item Restricted Investigating Factors Influencing Blockchain Adoption in Saudi Healthcare Data Management(Florida Institute of Technology, 2024-05-15) Alkhalifah, Noura; Slhoub, KhaledBlockchain technology can potentially address security and privacy issues concerning the collection, storage, and sharing of healthcare data. However, its adoption within the healthcare sector is nascent in Saudi Arabia. This underutilization prompted our investigation into the determinants influencing blockchain adoption, intending to fully empower the Saudi healthcare sector to leverage blockchain capabilities. To achieve this, an extensive literature review was conducted to identify the pivotal factors encompassing technology, organization, and environment (TOE) that affect the successful implementation of blockchain technologies in managing healthcare data within the Saudi context. Utilizing the TOE framework, this study formulated three hypotheses concerning the adoption of blockchain technology. Subsequently, a quantitative analysis was undertaken through an online survey distributed among healthcare organizations in Saudi Arabia. We obtained responses from 129 valid ques- tionnaires and employed a partial least squares structural equation model (PLS-SEM) for analysis and hypothesis testing. The results show that technological and organizational factors significantly influence the adoption of blockchains, whereas environmental factors have no significance. This study contributes significantly to bridging a critical gap in the academic literature by clarifying the factors influencing blockchain adoption in healthcare data management in Saudi Arabia. Our findings serve as valuable guidelines for decision-makers contemplating the adoption of blockchain technology in healthcare data management, thus facilitating the effective navigation of associated challenges.22 0Item Restricted Advancing Scalability, Efficiency, and Storage Optimization in Blockchain for Mobile Internet of Things (mIoT) Applications(2023) Zangoti, Hussein; Pissinou, Niki; Iyengar, Sundaraja Sitharama; Pan, Deng; Bobadilla, Leonardo; Andrian, Jean; Khan, Wazir ZadaThe increasing adoption of blockchain technology in mobile Internet of Things (mIoT) networks requires the development of blockchain systems that are efficient, scalable, and optimized for resource utilization. While several studies have attempted to address these challenges, comprehensive solutions that adapt to the inherent mobility of mIoT systems are still lacking. This Ph.D. thesis investigates three innovative methods to advance the current blockchain model for mIoT systems. First, a novel k-dimensional spatiotemporal, multidimensional, graph-based blockchain structure is introduced to address network partitioning issues caused by the mobility of IoT devices. This unique structure effectively manages blockchain nodes as they move between cell areas, resulting in smaller independent peer-to-peer subnetworks, each with its own blockchain copy. Experimental results demonstrate improved scalability and efficiency, with logarithmic growth as the blockchain size increases. Furthermore, the longest chain length is reduced by over 99.99% compared to traditional chain-based structures, making blockchain operations such as block appending or management more efficient. Building upon the multidimensional blockchain foundation, the next stage of this research involves developing an efficient merging algorithm for graph-based or multidimensional blockchains in mIoT networks. This algorithm addresses the challenge of merging partitioned blockchains that contain similar or identical blocks, which often require significant time and computational resources during the merging process. By leveraging depth-first search and Merkle tree techniques, the merging algorithm minimizes the time and computational resources spent on identical blocks, resulting in a 72% reduction in merging time compared to algorithms that do not handle block similarity. Lastly, considering the limited storage capacity of mIoT systems, this thesis presents a novel Collective Signing-Based Blockchain Storage Optimization (CSBSO) model aimed at minimizing storage overhead in resource-constrained mIoT systems. The model utilizes the existing Collective Signing (CoSi) protocol to reduce storage requirements and leverages a multidimensional blockchain structure for efficient block management and retrieval. The storage optimization approach identifies and prunes the most irrelevant blocks based on the CoSi protocol. Evaluations using real-world datasets, such as the Ethereum Classic Blockchain and Facebook users datasets, demonstrate that the CSBSO model outperforms state-of-the-art storage optimization models, achieving approximately 92% storage space savings. These results underscore the potential of CoSi-based storage optimization in effectively reducing blockchain storage overhead in resource-limited applications.30 0