Search Results (3,737)

The transportation industry has been recognized as one of the industries that can benefit from investment in blockchain-based systems and services that enable distributed data management and improve the effectiveness and efficiency of the transportation sector. However, the literature needs a guiding framework for integrating blockchain in issuing and preserving public transportation transactions in a technical environment that is secure, efficient, and transparent. This study proposes a blockchain-based transportation wallet (BTW) framework that facilitates the main digital transactions across diverse public transportation services. BTW embodies leveraging blockchain technology, which provides a decentralized and immutable ledger that records and verifies transactions, ensuring trust and reducing the risk of fraud. The framework has been validated by developing a blockchain-based public transportation smart wallet named “RideChain”. This serves as a single decentralized point for making public transportation transactions and payments, as well as identity authorizations and management. RideChain enhances passengers’ and service providers’ experience through a secure and authentic platform for offering several reliable public transportation transactions efficiently. In this study, we implemented a smart contract to establish a protocol between passengers and journey services. The testing methodologies used in this study comprise unit testing, integration testing, performance testing, and user acceptance testing. The findings suggest that BTW has been successfully verified to demonstrate its capability for secure transactions, authenticity of monetary transactions, automated smart contracts, decentralized identity authentication, and effortless payments. Full article

The Internet of Medical Things (IoMT) is a rapidly expanding network comprising medical devices, sensors, and software that collect and exchange patient health data. Today, the IoMT has the potential to revolutionize healthcare by offering more personalized care to patients and improving the efficiency of healthcare delivery. However, the IoMT also introduces significant privacy concerns, particularly regarding data privacy. IoMT devices often collect and store large amounts of data about patients’ health. These data could be used to track patients’ movements, monitor their health habits, and even predict their future health risks. This extensive data collection and surveillance could be a major invasion of patient privacy. Thus, privacy-preserving research in an IoMT context is an important area of research that aims to mitigate these privacy issues. This review paper comprehensively applies the PRISMA methodology to analyze, review, classify, and compare current approaches of preserving patient data privacy within IoMT blockchain-based healthcare environments. Full article

Population growth and environmental burden have turned the efforts of cities globally toward smarter and greener mobility. Cooperative and Connected Automated Mobility (CCAM) serves as a concept with the power and potential to help achieve these goals building on technological fields like Internet of Things, computer vision, and distributed computing. However, its implementation is hindered by various challenges covering technical parameters such as performance and reliability in tandem with other issues, such as safety, accountability, and trust. To overcome these issues, new distributed and decentralized approaches like blockchain and smart contracts are needed. This paper identifies a comprehensive inventory of CCAM challenges including technical, social, and ethical challenges. It then describes the most prominent methodologies using blockchain and smart contracts to address them. A comparative analysis of the findings follows, to draw useful conclusions and discuss future directions in CCAM and relevant blockchain applications. The paper contributes to intelligent transportation systems’ research by offering an integrated view of the difficulties in substantiating CCAM and providing insights on the most popular blockchain and smart contract technologies that tackle them. Full article

The increasing complexity of modern aircraft systems necessitates advanced monitoring solutions to ensure operational safety and efficiency. Traditional aircraft health monitoring systems (AHMS) often rely on reactive maintenance strategies, detecting only visible faults while leaving underlying issues unaddressed. This gap can lead to critical failures and unplanned downtime, resulting in significant operational costs. To address this issue, this paper proposes the integration of artificial intelligence (AI) and blockchain technologies within an enhanced AHMS, utilizing the iceberg model as a conceptual framework to illustrate both visible and hidden defects. The model highlights the importance of detecting and addressing issues at the earliest possible stages, ensuring that hidden defects are identified and mitigated before they evolve into significant failures. The rationale behind this approach lies in the need for a predictive maintenance system capable of identifying and mitigating hidden risks before they escalate. Key tasks completed in this study include: a comparative analysis of the proposed system with existing monitoring solutions, the selection of AI algorithms for fault prediction, and the development of a blockchain-based infrastructure for secure, transparent data sharing. The evolution of AHMS is discussed, emphasizing the shift from traditional monitoring to advanced, predictive, and prescriptive maintenance approaches. This integrated approach demonstrates the potential to significantly improve fault detection, optimize maintenance schedules, and enhance data security across the aviation industry. Full article

Cryptocurrencies have now become an emerging blockchain-based payment technology; among them, bitcoin is the best known and most widely used. Users on these networks are pseudo-anonymous, meaning that while all transactions from an address are transparent and searchable by anyone, the users’ true identities are not directly revealed; to preserve their privacy, users often use many different addresses. In recent years, some studies have been conducted regarding analyzing clusters of bitcoin addresses that, according to certain heuristics, belong to the same entity. This capability provides law enforcement with valuable information for investigating illegal activities involving cryptocurrencies. Clustering methods that rely on a single heuristic often fail to accurately and comprehensively cluster multiple addresses. This paper proposes Bitcoin Address Clustering based on multiple Heuristics (BACH): a tool that uses three different clustering heuristics to identify clusters of bitcoin addresses, which are displayed through a three-dimensional graph. The results lead to several analyses, including a comparative evaluation of WalletExplorer, which is a similar address clustering tool. BACH introduces the innovative feature of visualizing the internal structure of clusters in a graphical format. The study also shows how the combined use of different heuristics provides better results and more complete clusters than those obtained from their individual use. Full article

Advancements in blockchain technology and network technology are bringing in a new era in electronic voting systems. These systems are characterized by enhanced security, efficiency, and accessibility. In this paper, we compose a comparative analysis of blockchain-based electronic voting (e-voting) systems using blockchain technology, cryptographic techniques, counting methods, and security requirements. The core of the analysis involves a detailed examination of blockchain-based electronic voting systems, focusing on the variations in architecture, cryptographic techniques, vote counting methods, and security. We also introduce a novel blockchain-based e-voting system, which integrates advanced methodologies, including the Borda count and Condorcet method, into e-voting systems for improved accuracy and representation in vote tallying. The system’s design features a flexible and amendable blockchain structure, ensuring robustness and security. Practical implementation on a Raspberry Pi 3 Model B+ demonstrates the system’s feasibility and adaptability in diverse environments. Our study of the evolution of e-voting systems and the incorporation of blockchain technology contributes to the development of secure, transparent, and efficient solutions for modern democratic governance. Full article

The trinity of global warming, climate change, and air pollution casts an ominous shadow over society and the environment. At the heart of these threats lie carbon emissions, whose reduction has become paramount. Blockchain technology and the internet of things (IoT) emerge as innovative tools for establishing an efficient carbon credit exchange. This paper presents a blockchain and IoT-centric platform for carbon credit exchange, paving the way for transparent, secure, and effective trading. IoT devices play a pivotal role in monitoring and verifying carbon emissions, safeguarding the integrity and accountability of the trading process. Blockchain technology, with its decentralized and immutable nature, empowers the platform with transparency, reduced fraud, and enhanced accountability. This platform aims to arm organizations and individuals with the ability to actively curb carbon emissions, fostering collective efforts towards global pollution reduction goals. Full article

Software-Defined Networking (SDN) has emerged as a revolutionary architecture in computer networks, offering comprehensive network control and monitoring capabilities. However, securing the east–west interface, which is crucial for communication between distributed SDN controllers, remains a significant challenge. This study proposes a novel blockchain-based security framework that integrates Ethereum technology with customized blockchain algorithms for authentication, encryption, and access control. The framework introduces decentralized mechanisms to protect against diverse attacks, including false data injection, man-in-the-middle (MitM), and unauthorized access. Experimental results demonstrate the effectiveness of this framework in securing distributed controllers while maintaining high network performance and low latency, paving the way for more resilient and trustworthy SDN infrastructures. Full article

In the Internet of Things (IoT), the selection of mobile users with IoT-enabled devices plays a crucial role in ensuring the efficiency and accuracy of data collection. The reputation of these mobile users is a key indicator in selecting high-quality participants, as it directly reflects the reliability of the data they submit and their past performance. However, existing approaches often rely on a trusted centralized server, which can lead to single points of failure and increased vulnerability to attacks. Additionally, they may not adequately address the potential manipulation of reputation scores by malicious entities, leading to unreliable and potentially compromised user selection. To address these challenges, we propose PRUS, a privacy-preserving and quality-aware user selection scheme for IoT. By leveraging the decentralized and immutable nature of the blockchain, PRUS enhances the reliability of the user selection process. The scheme utilizes a public-key cryptosystem with distributed decryption to protect the privacy of users’ data and reputation, while truth discovery techniques are employed to ensure the accuracy of the collected data. Furthermore, a privacy-preserving verification algorithm using reputation commitment is developed to safeguard against the malicious tampering of reputation scores. Finally, the Dirichlet distribution is used to predict future reputation values, further improving the robustness of the selection process. Security analysis demonstrates that PRUS effectively protects user privacy, and experimental results indicate that the scheme offers significant advantages in terms of communication and computational efficiency. Full article

This article proposes a novel method for managing usage counters within an anonymous credential system, addressing the limitation of traditional anonymous credentials in tracking repeated use. The method takes advantage of blockchain technology through Smart Contracts deployed on the Ethereum network to enforce a predetermined maximum number of uses for a given credential. Users retain control over increments by providing zero-knowledge proofs (ZKPs) demonstrating private key possession and agreement on the increment value. This approach prevents replay attacks and ensures transparency and security. A prototype implementation on a private Ethereum blockchain demonstrates the feasibility and efficiency of the proposed method, paving the way for its potential deployment in real-world applications requiring both anonymity and usage tracking. Full article

Blockchain technology (BT) is a promising solution to address information asymmetry and trust issues in the prefabricated construction supply chain (PCSC). However, its practical application in PCSC remains limited under the influence of stakeholders’ adoption strategies. While previous studies have analyzed drivers and barriers to BT adoption, they often take a static view, neglecting the long-term dynamic decision-making interactions between stakeholders. This study addresses this gap by examining the interests of owners, general contractors, and subcontractors, and by developing a tripartite evolutionary game model to analyze the interaction mechanism of the strategy of adopting BT in PCSC. Additionally, a system dynamics simulation validates the evolution of stabilization strategies and examines the impact of key parameters. The results indicate that successful BT adoption requires technology maturity to surpass a threshold between 0.5 and 0.7, along with a fair revenue and cost-sharing coefficient between general contractors and subcontractors, ranging from 0.3 to 0.5 at the lower limit and 0.7 to 0.9 at the upper limit. Notably, general contractors play a pivotal role in driving BT adoption, acting as potential leaders. Furthermore, appropriate incentives, default compensation, and government subsidies can promote optimal adoption strategies, although overly high incentives may reduce owners’ willingness to mandate BT adoption. This study provides practical insights and policy recommendations for critical stakeholders to facilitate the widespread adoption of BT in PCSC. Full article

The use of smart contracts in areas such as finance, supply chain management, and the Internet of Things has significantly advanced blockchain technology. However, once deployed on the blockchain, smart contracts cannot be modified or revoked. Any vulnerabilities can lead to severe economic losses and data breaches, making pre-deployment vulnerability detection critically important. Traditional smart contract vulnerability detection methods suffer from low accuracy and limited reusability across different scenarios. To enhance detection capabilities, this paper proposes a smart contract vulnerability detection method based on heterogeneous contract semantic graphs and pre-training techniques. Compared to the conventional graph structures used in existing methods, heterogeneous contract semantic graphs contain richer contract information. By integrating these with pre-trained models, our method exhibits stronger vulnerability capture and generalization capabilities. Experimental results show that this method has improved the accuracy, recall, precision, and F1 value in the detection of four widely existing and harmful smart contract vulnerabilities compared with existing methods, which greatly improves the detection ability of smart contract vulnerabilities. Full article

6G mobile network technology will set new standards to meet performance goals that are too ambitious for 5G networks to satisfy. The limitations of 5G networks have been apparent with the deployment of more and more 5G networks, which certainly encourages the investigation of 6G networks as the answer for the future. This research includes fundamental privacy and security issues related to 6G technology. Keeping an eye on real-time systems requires secure wireless sensor networks (WSNs). Denial of service (DoS) attacks mark a significant security vulnerability that WSNs face, and they can compromise the system as a whole. This research proposes a novel method in blockchain 6G-based wireless network security management and optimization using a machine learning model. In this research, the deployed 6G wireless sensor network security management is carried out using a blockchain user datagram transport protocol with reinforcement projection regression. Then, the network optimization is completed using artificial democratic cuckoo glowworm remora optimization. The simulation results have been based on various network parameters regarding throughput, energy efficiency, packet delivery ratio, end–end delay, and accuracy. In order to minimise network traffic, it also offers the capacity to determine the optimal node and path selection for data transmission. The proposed technique obtained 97% throughput, 95% energy efficiency, 96% accuracy, 50% end–end delay, and 94% packet delivery ratio. Full article

The online services provided by the Service Provider (SP) have brought significant convenience to people’s lives. Nowadays, people have grown accustomed to obtaining diverse services via the Internet. However, some SP utilize or even tamper with personal data without the awareness or authorization of the Data Provider (DP), a practice that seriously undermines the authenticity of the DP’s authorization and the integrity of personal data. To address this issue, we propose a Verifiable Authorization Information Management Scheme (VAIMS). During the authorization process, the authorization information and personal data fingerprints will be uploaded to the blockchain for permanent record, and then the SP will store such authorization information and personal data. The DP generates corresponding authorization fingerprints based on the authorization information and stores them independently. Through the authorization information and authorization fingerprints on the chain, the DP can verify the authenticity of the authorization information stored by the SP at any time. Meanwhile, by leveraging the personal data fingerprint on the blockchain, the DP can check whether the personal data stored by the SP has been tampered with. Additionally, the scheme incorporates database technology to accelerate data query. We implemented a VAIMS prototype on Etherum, and experiments demonstrate that the scheme is effective. Full article

Assembly Theory provides a promising framework to explain the complexity of systems such as molecular structures and the origins of life, with broad applicability across various disciplines. In this study, we explore and consolidate different aspects of Assembly Theory by introducing a simplified Toy Model to simulate the autocatalytic formation of complex structures. This model abstracts the molecular formation process, focusing on the probabilistic control of catalysis rather than the intricate interactions found in organic chemistry. We establish a connection between probabilistic catalysis events and key principles of Assembly Theory, particularly the probability of a possible construction path in the formation of a complex object, and examine how the assembly of complex objects is impacted by the presence of autocatalysis. Our findings suggest that this presence of autocatalysis tends to favor longer consecutive construction sequences in environments with a low probability of catalysis, while this bias diminishes in environments with higher catalysis probabilities, highlighting the significant influence of environmental factors on the assembly of complex structures. Full article