The ongoing human organ transplantation system has some limitations. These include waiting times, ways of allocating organs, and a lack of information sharing among different institutions. These issues lead to some problems, lack of transparency, and also ethical concerns, to some extent. However, every system now can be improved through the use of technology. Blockchain offers Cryptographic hash functions, Digital signatures, Proof of work, double spend problem, Decentralization, Distributed network, Merkle Trees that can address these challenges and transform the organ transplantation process. This paper suggests a framework called B-HOTMS (Blockchain-based Human Organ Transplantation Management System) that aims to improve transparency, better communication and prioritize organ registration process. B-HOTMS uses a permissioned blockchain network along with contracts to automate tasks. This system also confirms data privacy and provides a user-friendly interface for all stakeholders. The application of B-HOTMS can be beneficial to the whole process as it shortens the time of waiting, enhances the level of transparency, leading to the trust and accountability of the stakeholders, improves data security and privacy while, and facilitates the communication among the stakeholders. Collaboration with legal bodies is crucial to ensure compliance with existing regulations while integrating technology into the process. Lastly, addressing concerns will be vital for the implementation of B-HOTMS so that it aligns with moral principles while saving more lives in an efficient manner. In conclusion by harnessing the potential offered by technology, we can envision a future where organ transplantation becomes efficient, transparent and ethical, leading to saving more lives.
S M Habibullah, Sahabul Alam, Shivnath Ghosh, Arindam Dey · 5 authors
Blockchain is a decentralized electronic account book that is secure, open, and impervious to manipulation, and records transactions across numerous computers. Internet of Things (IoT) deployed sensors are limited in bandwidth, processing power, and battery life. Energy efficiency is a vital factor and a decisive matter for energy-bound IoT-based networks. This paper provides an idea of the working principle of blockchain technology in IoT-enabled energy systems. It investigates the fundamentals of blockchain technology, clarifying its decentralized nature, cryptographic mechanisms, and consensus algorithms that ensure data immutability and transparency. It explores how blockchain technology can be integrated with various IoT fields for energy efficiency. The paper investigates the blockchain-based energy consumption approaches in IoT qualitatively, and quantitatively with future research directions and challenges. It is seen that the hybrid blockchain model is suitable for energy efficiency in IoT.
Ranjith Kumar Chinnam, K. Babu, B. Srinivas, A. Satyam · 6 authors
Current research has engrossed on the potential of the blockchain system to resolve security concerns in the IoT net. However, blockchain's intrinsic scalability problems become noticeable in environments with a high volume of data created by a significant number of Internet of Things (IoT) devices. In this work, researchers used an efficient consensus technique to overcome these challenges. For the management of data generated by the Internet of Things, we propose a scalable solution based on blockchain technology. This framework ensures enhanced efficiency and effectiveness in Internet of Things networks using constrained resources by using the delegation Proof of Stake (DPoS) consensus approach. To lessen the load on blockchain-based IoT networks, DPoS allows just a select group of chosen delegates to verify and approve transactions. To facilitate distributed storage, the investigators in this study constructed the Interplanetary File System (IPFS), and they also developed a Docker system to gauge net presentation in terms of latency, productivity, and source use. Distributed stored latency, throughput, utilization of resources, and file upload length and speed were the four areas that researchers examined in our inquiry. Empirical results from researchers show that our approach has a minimal latency of less than 0.977 Ms the suggested method works better than Proof of Stake (PoS), which is considered to be the most advanced consensus method. Researchers further show that the suggested method might be helpful in Internet of Things applications that need to be resource-efficient or low latency.
As unmanned aerial vehicle (UAV) technology expands into diverse applications, the demand for enhanced performance intensifies. Blockchain sharding technology offers promising avenues for improving data processing capabilities and security in drone networks. However, the inherent mobility of UAVs and their dynamic operational environment pose significant challenges to conventional sharding techniques, often resulting in communication latencies and data synchronization delays that compromise efficiency. This study presents a novel blockchain-based adaptive sharding framework specifically designed for UAV ecosystems. Our research extends beyond improving data transmission rates to encompass an enhanced Asynchronous Advantage Actor-Critic algorithm, tailored to address long-term optimization objectives in aerial networks. The proposed optimizations focus on dual objectives: enhancing data security while concurrently accelerating processing speeds. By addressing the limitations of traditional approaches, this work aims to facilitate seamless communication and foster innovation in UAV networks. The adaptive sharding framework, coupled with the refined A3C algorithm, presents a comprehensive solution to the unique challenges faced by mobile aerial systems in blockchain implementation.
Aleika Lwiza Alves Fonsêca, Ingridy M. P. Barbalho, Felipe Fernandes, Ernano Arrais Júnior · 14 authors
(1) Background: With the increasing digitalization of healthcare systems, data security and privacy have become crucial issues. In parallel, blockchain technology has gradually proven to be an innovative solution to address this challenge, as its ability to provide an immutable and secure record of transactions offers significant promise for healthcare information management. This systematic review aims to explore the applications of blockchain in health information systems, highlighting its advantages and challenges. (2) Methods: The publications chosen to compose this review were collected from six databases, resulting in the initial identification of 4864 studies. Of these, 73 were selected for in-depth analysis. (3) Results: The main results show that blockchain has been used mainly in electronic health records (63%). Furthermore, it was used in the Internet of Medical Things (8.2%) and for data sharing during the COVID-19 pandemic (6.8%). As advantages, greater security, privacy, and data integrity were identified, while the challenges point to the need for standardization and regulatory issues. (4) Conclusions: Despite the difficulties encountered, blockchain has significant potential to improve healthcare data management. However, more research and continued collaboration between those involved are needed to maximize its benefits.
The food industry offers diverse supply chains with multiple locations for manufacturers, dealers, and customers. The techniques of distribution and transaction used in online food trade are currently unclear. This problem, along with participants' unwillingness to offer information and lack of confidence, presents significant issues for the global food supply chain industry. The goal of this project is to build a blockchain-based Food Supply Chain (FSC) architecture that will enable the tracking of food from the farm to the customer transparently and safely. The suggested method encourages openness and wellinformed decision-making by tracking participant interactions, triggering events, and logging transactions using Ethereum smart contracts. Smart contracts also control how vendors and customers communicate, for example, by keeping track of and alerting customers about the condition of Internet of Things (IoT) containers used in food supply chains. To improve transparency and immutability, the suggested framework might be expanded to include other supply chain industries in the future.
Linchao Zhang, Lei Hang, Keke Zu, Yi Wang · 5 authors
As smart cities rapidly evolve, the Vehicle-to-Everything (V2X) network faces significant challenges in data security and communication efficiency. This paper introduces an innovative algorithm based on a reputation mechanism, named the Dynamic Vehicle Reputation Consensus (DVRC), which focuses on improving the data security and communication efficiency of vehicular networks using blockchain technology. The DVRC algorithm comprehensively assesses vehicle behaviors and the consensus contribution within the blockchain network, utilizing a reputation scoring system to evaluate the reliability within the network. Furthermore, this study delves into multimodal communication strategies in vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) scenarios. Notably, when vehicles leave the range of basic infrastructure, those with high reputation scores (as determined by the DVRC's reputation values) relay the communication service. Additionally, the introduction of a reputation incentive mechanism and dynamic consensus threshold adjustments aim to improve consensus efficiency and encourage honest behavior. Experimental results demonstrate that the DVRC algorithm significantly improves communication efficiency in blockchain-based vehicular networks, such as increased throughput, reduced latency, and improved network scalability. These advances have substantial theoretical and practical significance for the development of vehicular networks in smart cities.
Koustav Kumar Mondal, Ashi Gupta, Debasis Das, Chun‐I Fan
This research introduces PISTON, a novel protocol designed to enhance the security, efficiency, and performance of Internet of Vehicles (IoV) networks. PISTON integrates advanced authentication mechanisms utilizing Physically Unclonable Functions (PUFs) and multifactor authentication with dynamic challenges and zero-knowledge proof-based authentication to ensure robust security and mitigate various cyber threats, including Denial-of-Service (DoS) attacks. The protocol further incorporates sleep-wake scheduling, priority-based scheduling, and adaptive modulation and coding to optimize network performance. The communication overhead in PISTON is derived through a formula that incorporates latency, energy consumption, and throughput, demonstrating the protocol’s efficiency in dynamic vehicular environments. Comparative analysis against existing protocols highlights PISTON’s superiority in seamless handover, provable security, and DoS attack resilience. Experimental results show that PISTON reduces energy consumption by 30% and achieves 20% higher data throughput while maintaining low latency, essential for real-time IoV applications. The empirical findings underscore PISTON’s advancements in establishing a new benchmark for future IoV deployments, ensuring secure, energy-efficient, low-latency, and high-throughput communication.
The Internet of Ships (IoS), by integrating advanced technologies, such as the Internet of Things, cloud computing, and artificial intelligence, aims to interconnect and communicate various physical devices related to maritime transportation, including ships, ports, traffic infrastructure, and warehouses. This integration is designed to optimize transportation decision making, reduce costs, enhance efficiency, improve safety, and promote environmental sustainability. Traditional IoS adopts a cloud computing-based data processing and service model, which, due to its centralized and remotely deployed nature, often places computing nodes far from the data collection and service demand points. This setup struggles to meet the high real-time and low-latency requirements of intelligent ships, traffic organization, remote control, and other applications. Edge computing, by decentralizing computing, storage, and network resources to the edge of the IoS, enables more responsive handling of device requests. It addresses critical requirements, such as intelligent access, real-time communication, and privacy protection in the IoS environment, facilitating intelligent, green communication, efficient data processing, and timely service responses. In this article, the current state of IoS and the relevant concepts of edge computing are introduced. The edge computing enabling IoS (EC-IoS) architecture and the core technologies driving EC-IoS development are systematically discussed. Emerging applications and the case studies of EC-IoS, including intelligent ships at different autonomy levels, intelligent transportation, smart ports, and warehouses, are summarized. Finally, challenges and future opportunities in open computing environments, maritime data management, system security, and resource management are outlined, providing a reference for optimizing maritime management and autonomous navigation.
The increasing ability of internet-connected daily life electronic gadgets has propelled smart homes into a global trend. The Internet of Things (IoT) enables ambient devices to communicate and interact seamlessly through various sensors. Emerging technical concepts like Web3 and Industry 5.0 require decentralised and intelligent systems near the network's edge. Petabytes of IoT sensor-generated data cause a shortage of storage on the Cloud servers, adding a delay factor to the IoT system. Standard cloud-based IoT systems can't fully function in areas with unstable internet. This paper addresses these challenges and proposes a solution to integrate edge computing concepts. The proposed system is developed using a Raspberry Pi 3 Home Server (RHS) driven by the Support Vector Machine (SVM) algorithm. The designed prototype includes a fire and smoke detection system with MQ2 gas, dust, temperature, and flame sensors. The SVM and these sensors form a data fusion module integrating with Network Mapper (NMAP), Message Queuing Telemetry Transport (MQTT) broker, MariaDB SQL server, and InfluxDB time series database. The experiments demonstrate a fundamental edge operation with a latency of 2.45 ms (milliseconds), while NMAP integration ensures data security and device verification for sensor data storage. The synthetic simulations show positive outcomes for the data fusion-based monitoring system, where alerts are promptly triggered as sensor values change, with an overall system latency of approximately 24 ms. The developed system manages home automation, real-time monitoring for fire, smoke, gas leaks, network scans, anomaly detection, appliance usage tracking, and cloud data backup. A multi-level alert system ensures early threat mitigation, with alarms, SMS, notifications, and email alerts to maximize awareness.
Mohamed Moetez Abdelhamid, Layth Sliman, Raoudha Ben Djemaa
Purpose: The integration of AI with blockchain technology is investigated in this study to address challenges in IoT-based supply chains, specifically focusing on latency, scalability, and data consistency. Background: Despite the potential of blockchain technology, its application in supply chains is hindered by significant limitations such as latency and scalability, which negatively impact data consistency and system reliability. Traditional solutions such as sharding, pruning, and off-chain storage introduce technical complexities and reduce transparency. Methods: This research proposes an AI-enabled blockchain solution, ABISChain, designed to enhance the performance of supply chains. The system utilizes beliefs, desires, and intentions (BDI) agents to manage and prune blockchain data, thus optimizing the blockchain’s performance. A particle swarm optimization method is employed to determine the most efficient dataset for pruning across the network. Results: The AI-driven ABISChain platform demonstrates improved scalability, data consistency, and security, making it a viable solution for supply chain management. Conclusions: The findings provide valuable insights for supply chain managers and technology developers, offering a robust solution that combines AI and blockchain to overcome existing challenges in IoT-based supply chains.
M. Shakila, S. Pandiaraj, S P Sharmila, Tanesh Kumar · 6 authors
Decentralized and promising, blockchain technology brings enhanced security for data along with privacy issues particularly in health and supply chains. Here, we aim to show the usage of blockchain towards the secure data of devices that come under Internet of Medical Things or IoMT by providing data integrity and further sensitive medical information protection. A secure, transparent, and tamper-proof system in health care management can be supported by an IoT framework that uses blockchain. Four data security and privacy algorithms based on blockchain have been considered and tested with excellent results to show a clear indication of how much prevention in un-authorized access can be done in ensuring authenticity, tracking products in the medical supply chain. Some experiments were demonstrated where the blockchain-enabled system had reduced the data breach by 95% from traditional systems. Supply chain traceability had improved by 92%. The combination of machine learning and blockchain increased real-time threat detection by 88%. The outcome shows that blockchain can deal with problems like tampering, privacy violation, and counterfeiting in medical products. However, scalability of applications and adoption by regulators are two major challenges towards full integration. This paper aids in the development of a complete holistic framework that may make use of the usage of blockchain to secure health care and other supply chain systems to allow further avenues for digitizing data safety.
Ehtisham Ul Haque, Waseem Abbasi, Ahmad Almogren, Jaeyoung Choi · 7 authors
The proliferation of Internet of Things (IoT) devices generates vast amounts of data, traditionally stored, processed, and analyzed using centralized systems, making them susceptible to attacks. Blockchain offers a solution by storing and securing IoT data in a distributed manner. However, the low performance and poor scalability of blockchain technology pose significant challenges for its application in IoT networks. The primary obstacle is the distributed consensus protocol, while ensuring data transparency, integrity, and immutability in a decentralized and untrusted circumstances which often compromises scalability. To address this issue, this paper introduces the use of the Delegated Proof of Stake (DPoS) consensus algorithm and sharding techniques to enhance scalability in blockchain-based IoT networks. Experimental results indicate that system throughput increases synchronously with the test load. Our findings reveal a tradeoff between throughput, latency, and up-downstream time on the Inter Planetary File System (IPFS). Given the critical importance of latency and throughput in IoT networks, the results demonstrate that DPoS offers high throughput, parallel processing, and robust security while efficiently scaling the network. Furthermore, at a test load of 500 Transactions Per Second (TPS), the system achieves a maximum throughput of approximately 11.094 ms. However, when the test load exceeds 2000 TPS, the total processing time for transactions extends to 11.205 ms. This method is particularly suitable for constrained IoT networks. Compared to previous edge computing-based approaches, our scheme demonstrates superior throughput performance.
Blockchain interoperability protocols enable cross-chain asset transfers or data retrievals between isolated chains, which are considered as the core infrastructure for Web 3.0 applications such as decentralized finance protocols. However, existing protocols either face severe scalability issues due to high on-chain and off-chain costs, or suffer from trust concerns because of centralized designs. In this paper, we propose \texttt{MAP}, a trustless blockchain interoperability protocol that relays cross-chain transactions across heterogeneous chains with high scalability. First, within \texttt{MAP}, we develop a novel \textit{cross-chain relay} technique, which integrates a unified relay chain architecture and on-chain light clients of different source chains, allowing the retrieval and verification of diverse cross-chain transactions. Furthermore, we reduce cross-chain verification costs by incorporating an optimized zk-based light client scheme that adaptively decouples signature verification overheads from inefficient smart contract execution and offloads them to off-chain provers. For experiments, we conducted the first large-scale evaluation on existing interoperability protocols. With \texttt{MAP}, the required number of on-chain light clients is reduced from $O(N^2)$ to $O(N)$, with around 35\% reduction in on-chain costs and 25\% reduction for off-chain costs when verifying cross-chain transactions. To demonstrate the effectiveness, we deployed \texttt{MAP} in the real world. By 2024, we have supported over six popular public chains, 50 cross-chain applications and relayed over 200K cross-chain transactions worth over 640 million USD. Based on rich practical experiences, we constructed the first real-world cross-chain dataset to further advance blockchain interoperability research.
Ningyuan Chen, Chiew Foong Kwong, David Chieng, Pushpendu Kar
The advent of Cellular Vehicle-to-Everything (C-V2X) technology has revolutionized intelligent transportation systems (ITS), but poses challenges for secure and efficient data sharing due to its dynamic nature. Traditional centralised systems are inadequate, prompting the need for decentralised solutions like blockchain. However, applying blockchain technologies in C-V2X always faces scalability issues. This paper proposes a scalable C-V2X blockchain network integrating dynamic attribute-based sharding and zero-knowledge proofs (ZKPs). Our system ensures scalability in the C-V2X environment through sharding while utilising ZKPs to enhance cross-shard validation efficiency, reducing its complexity to O(1). Additionally, our approach reduces bandwidth consumption by 90.8% compared to Merkle tree-based solutions.
The integration of blockchain technology into compliance auditing presents a transformative opportunity for enhancing Governance, Risk, and Compliance (GRC) mechanisms within hybrid cloud IT governance frameworks. This review explores the potential of blockchain to address long-standing challenges in auditability, transparency, and trust across distributed and heterogeneous computing environments. By leveraging blockchain’s immutable ledger, smart contract automation, and decentralized consensus protocols, organizations can ensure real-time verification of compliance activities, secure audit trails, and enforceable policy adherence across cloud infrastructures. The paper critically evaluates existing literature on blockchain-enabled compliance auditing, identifies gaps in current GRC integration practices within hybrid cloud ecosystems, and discusses emerging frameworks that align regulatory compliance with dynamic IT operations. Key challenges such as interoperability, scalability, and regulatory acceptance are analyzed alongside opportunities for enhanced accountability, cross-border compliance, and audit automation. The review concludes by outlining future research directions, emphasizing the need for standardized blockchain-GRC interfaces, regulatory sandboxing, and industry-specific implementation models to fully realize the benefits of blockchain in hybrid cloud IT governance.
IOTA is an emerging decentralized computing paradigm for developing blockchain-based Internet of Things (IoT) applications. It has the advantages of zero transaction fees, incremental scalability, and high-performance transaction rates. Despite its well-understood benefits, IOTA nodes need to withstand considerable resource costs to generate the distributed ledger. The main reason for this is that IOTA abandons the original blockchain reward mechanism and does not charge transaction fees. Therefore, in this paper we address the cost optimization issue for IOTA based on Lyapunov optimization theory. We take the first step in investigating the cost optimization problem of IOTA and exploring a new optimization scheme using Lyapunov optimization theory. Our proposed scheme enables IOTA to minimize the total cost of IOTA nodes through a computational optimization algorithm. Then, an optimized transaction rate control algorithm can be designed based on the large deviation theory to reduce orphan tangles that waste computational costs. In addition, we define and deduce the effective width of the tangle to monitor the total throughput and reduce the time spent on cost optimization to avoid unnecessary waste of resources. Lastly, a comprehensive theoretical analysis and simulation experiments demonstrate that the proposed strategy is both efficient and practical.
The blockchain technology and its applications, such as cryptocurrencies or non-fungible tokens, represent significant advancements in computer science. Alongside its transformative potential, human interaction with blockchain has led to notable negative implications, including cybersecurity vulnerabilities, high energy consumption in mining activities, environmental impacts, and the prevalence of economic fraud and high-risk financial products. Considering the expanding range of blockchain applications, there is interest in exploring its integration into K-12 education. For this purpose, this paper examines existing and documented attempts through a systematic literature review. Although the findings are quantitatively limited, they reveal initial concepts and ideas.