Blockchain Papers

Abdullah Ayub Khan, Jing Yang, Asif Ali Laghari, Abdullah M. Baqasah · 9 authors

No abstract is available for this record.

Dipabali Nath, Parama Bhaumik

Managing blood screening data is critical for healthcare, requiring secure and transparent systems to safeguard public health. Existing methods often lack secure access to donors' medical histories, posing risks. Hyperledger Fabric, a distributed ledger technology, offers a robust solution for managing health data securely. This paper proposes a decentralized blood screening system using Hyperledger Fabric to record transactions, donor, and recipient data, employing chaincode for eligibility checks. Its modular architecture ensures privacy, integrity, and immutability. The study explores how Hyperledger Fabric's architecture meets blood screening requirements, focusing on optimizing latency, throughput, and block space utilization through customized configurations. Experiments with Hyperledger Fabric v2.5 assessed performance by adjusting endorsement strategies and block sizes. The results, analyzed for performance differences, provide recommendations for tuning configuration factors like batch timeout and maximum message count. The Hyperledger Caliper tool was used to measure transaction throughput and latency, leading to optimized blockchain architecture for blood screening. Findings indicate that customized blockchain configurations can significantly enhance performance metrics crucial for real-time healthcare applications.

Muskaan Mongia

Blockchain and cloud technologies together constitute a major breakthrough in distributed systems architecture since they provide companies with unheard-of security, scalability, and operational efficiency. The symbiotic relationship between blockchain's immutable ledger system and cloud computing's scalable infrastructure is investigated in this article together with how their convergence opens fresh opportunities for business applications in supply chain management, financial services, and healthcare sectors. By means of the analysis of important architectural patterns, including Blockchain-as-a-Service (BaaS) and hybrid storage solutions, it shows how this integration addresses conventional constraints while enabling creative features such as automated compliance, real-time settlement systems, and improved data management. The article also looks at technical issues in security, interoperability, and scalability and suggests ways to use the capabilities of both technologies. Emerging technologies like artificial intelligence and IoT combined with evolving industry standards point to a transforming effect on how companies handle and use data in the digital economy as this paradigm develops.

Peng Liu, Qian He, Yi‐Ting Chen, Shan Jiang · 6 authors

Intelligent Transport Systems are designed to revolutionize the performance and efficiency of Vehicular Ad Hoc Networks (VANETs). Consumer electronics encompassing autonomous driving and route planning contribute to a better driving experience. Federated learning enables vehicle collaboration to train global models of intelligent transport without sharing local data for personalized consumer electronics. However, due to the dynamic network topology and unreliable open channels of VANETs, various potential risks undermine the credibility of establishing intermediate model parameters. To address these issues, we propose a lightweight authentication and privacy-preserving aggregation scheme for blockchain-enabled federated learning in VANETs(LPBFL). Specifically, we first construct a distributed secure authentication framework for blockchain federated learning that facilitates seamless authentication of mobile vehicles and security of model transmission. Subsequently, we design a lightweight three-party authentication key agreement based on chaotic map that establishes a session key for secure transmission of the intermediate model. In addition, we propose a continuous authentication adaptive model aggregation algorithms to ensure local model integrity while improving the quality of global models. Finally, security analysis and proofs show that LPBFL enhances the privacy and reliability of intermediate model parameters. Comprehensive experimental evaluations substantiate that the proposed LPBFL facilitates lightweight authentication while maintaining superior model accuracy.

Pallav Gupta, Swarab Raul, S. Shoba, Karthika Veeramani

No abstract is available for this record.

Abdullah Ayub Khan, Asif Ali Laghari, Abdullah M. Baqasah, Rex Bacarra · 7 authors

The integration of artificial intelligence (AI) has caused information and communication technology (ICT) to undergo a number of recent rapid fluctuations. These changes have primarily affected the areas of management, end-to-end device interconnectivity, resource organization, communication, networking, and application-related aspects of ICT. Owing to the complex structure of applicational connectedness, evaluating each of the aforementioned opportunities concurrently reflects the idea of heterogeneity. The association of multiple end devices, particularly in interoperable space, integrity, privacy protection, security, provenance, and the massive volume of everyday media data generated in the modern healthcare setting could also provide significant issues. To address these issues, decentralized, secure, economical resource optimization, and intelligent network activities and organization are necessary. Blockchain technology plays a crucial role in providing distributed storage data organization, sharing, and exchange for automated decision-making, privacy, and security in AI-enabled machine learning (ML) models. However, machine learning models—support vector machine, in particular—have a significant impact on the growth of distributed consortium networks and the exchange of information among connected nodes, resolving issues with resource management, scalability, and data processing. By resolving the three main problems of seamless data integrity, peer-to-peer communication between nodes, and infrastructure security, we provide a novel interoperable technique in this proposed architecture. The approach is unique, as demonstrated by the simulation-based results, which display huge differences of 1.37%, 1.56%, and 1.87%, respectively. The background for the evaluation consists of the following three areas: (i) infrastructure security to protect automated decision-making; (ii) integrity between smooth data sharing and exchange; and (iii) network resource optimization to enable smooth communication across heterogeneous devices.

Kun Yan, Wenping Ma, Shaohui Sun

5G networks provide secure and reliable information transmission services for the Internet of Everything, thus paving the way for 6G networks, which is anticipated to be an AI-based network, supporting unprecedented intelligence across applications. Abundant computing resources will establish the 6G Computing Power Network (CPN) to facilitate ubiquitous intelligent services. In this article, we propose BECS, a computing sharing mechanism based on evolutionary algorithm and blockchain, designed to balance task offloading among user devices, edge devices, and cloud resources within 6G CPN, thereby enhancing the computing resource utilization. We model computing sharing as a multi-objective optimization problem, aiming to improve resource utilization while balancing other issues. To tackle this NP-hard problem, we devise a kernel distance-based dominance relation and incorporated it into the Non-dominated Sorting Genetic Algorithm III, significantly enhancing the diversity of the evolutionary population. In addition, we propose a pseudonym scheme based on zero-knowledge proof to protect the privacy of users participating in computing sharing. Finally, the security analysis and simulation results demonstrate that BECS can fully and effectively utilize all computing resources in 6G CPN, significantly improving the computing resource utilization while protecting user privacy.

Mritunjay Shall Peelam, Vinay Chamola, Biplab Sikdar

Blockchain technology, renowned for its ability to securely store data, hashes, and signatures permanently, faces unprecedented challenges in secure Consumer IoT (CIoT) networks with the advent of quantum computing. This paper proposes a set of robust quantum-based protocols and techniques to address these challenges by enhancing the security, scalability, and reliability of CIoT systems in the face of quantum threats. Updating the blockchain infrastructure is imperative to ensure ongoing security, which involves forks or protocol adjustments to establish new post-quantum chains and addresses, requiring rapid data and asset migration by users. Blockchain guarantees data integrity through an immutable ledger of transactions distributed via cryptographic hashes. The proposed quantum protocols and techniques enhance scalability and reliability and address the unique security needs of both commercial and governmental applications in secure CIoT networks through immersive embedded cyber-physical systems. These include Quantum Currency Security Protocols, Distributed Ledger Data Blocks, Quantum Ledger Verification, Quantum Solutions for Middleman Attacks, and the integration of Elliptic Curve Cryptography (ECC)-based security measures. By integrating these methods, the proposed approach ensures robust protection against emerging quantum threats, thereby securing sensitive information and transactions.

Shenoy Phalgun, M. Durga, Amit Dua, Gagangeet Singh Aujla · 5 authors

Different types of cryptocurrencies have surged rapidly in recent years, with recent trends in tokenization and memecoin. This growth highlights the cryptocurrency market’s rapid expansion, especially in token creation at decentralized exchanges (DEXs). At the same time, the evolution of artificial intelligence (AI) and Web3 presents significant challenges, including sustained user engagement in AI-driven applications while maintaining utility and scalability. Existing game theory-based methods often increase centralization and hence introduce security vulnerabilities. This hinders widespread adoption. To overcome these challenges, we propose Slinky Web3AI, a framework that integrates blockchain technology with AI to address these challenges. Slinky Web3AI supports long-term ecosystem development through a decentralized token creation mechanism and privacy-preserving incentive structures. Our proposed architecture demonstrates improved security, scalability, and efficiency, validated by experimental results. Slinky Web3AI provides a foundational framework for future AI and blockchain applications for future smart communities.

Ting Li, Anfeng Liu, Shaobo Zhang, Tian Wang · 5 authors

No abstract is available for this record.

Andreas Polyvios Delladetsimas, Stamatis Papangelou, Elias Iosif, George M. Giaglis

This review examines the integration of blockchain technology with the IoT in the Marine Internet of Things (MIoT) and Internet of Underwater Things (IoUT), with applications in areas such as oceanographic monitoring and naval defense. These environments present distinct challenges, including a limited communication bandwidth, energy constraints, and secure data handling needs. Enhancing BIoT systems requires a strategic selection of computing paradigms, such as edge and fog computing, and lightweight nodes to reduce latency and improve data processing in resource-limited settings. While a blockchain can improve data integrity and security, it can also introduce complexities, including interoperability issues, high energy consumption, standardization challenges, and costly transitions from legacy systems. The solutions reviewed here include lightweight consensus mechanisms to reduce computational demands. They also utilize established platforms, such as Ethereum and Hyperledger, or custom blockchains designed to meet marine-specific requirements. Additional approaches incorporate technologies such as fog and edge layers, software-defined networking (SDN), the InterPlanetary File System (IPFS) for decentralized storage, and AI-enhanced security measures, all adapted to each application’s needs. Future research will need to prioritize scalability, energy efficiency, and interoperability for effective BIoT deployment.

Krishna Kishor Tirupati, Imran Khan, Lalit Kumar, Srinivasulu Harshavardhan Kendyala · 6 authors

In this paper, we use blockchain technology to manage communication and trust between cars and the Internet of Vehicles (IoV). Data transmission between vehicles can be made secure, transparent, and tamper-proof thanks to blockchain's decentralized nature. A smart contract also enhances trust and accountability by incorporating consensus mechanisms such as proof of work and proof of stake. A two-part system is proposed, consisting of a vehicle registration module and a message alert module. In order to integrate new vehicles into the network, smart contracts have been developed, which are linked to the wallets of the users. Blockchain-based smart contracts facilitate secure vehicle registration. In the second module, message alert generation, an administrator can generate messages and send them to all registered vehicles via a web-based platform, with Ethereum gas costs covering the transaction fees. Blockchain technology is used to exchange data securely and reliably for self-driving cars. The consensus mechanism verifies data integrity through both proof of stake and proof of work, ensuring trustworthiness and transparency.

Rasha Halim Razzaq, Mishall Al-Zubaidie, Rajaa Ghali Atiyah

Protecting patient data in the Internet of Medical Things (IoMT) is one of the major challenges facing healthcare organizations because of increasing threats to privacy and security. Although there are many existing protocols and solutions, such as Rivest–Shamir–Adleman (RSA) and El-Gamal cryptographies or centralized methods, that aim to protect data, they suffer from weaknesses such as slow performance or inability to handle large volumes of data. The issue of security in medical records has become an urgent need, and the use of centralized methods can expose them to single-point failure. In this paper, we present the efficient approach to securing patient information (EASPI), which depends on blockchain and integrates innovative techniques such as the advanced encryption algorithm (AES), reverse word frequency analysis (TF-IDF), Lemplel-Ziv-Welch (LZW), decision tree model (DTM), and naive Bayes classifier (NBC). EASPI seeks to improve the security of medical data by storing it encrypted and securely via blockchain technology, providing a high level of privacy and reliability. The experimental results indicate that the EASPI reduces the encryption execution time to 0.2 ms and the decryption execution time to 0.3 ms while improving the accuracy of medical diagnosis. The potential of the suggested methods for healthcare systems is further demonstrated by the fact that the TF-IDF algorithm attained an execution time of 0.004 ms, while the blockchain's greatest execution time was 0.014 ms. Additionally, using the formal verification Scyther tool, the security of the suggested system is examined both theoretically and practically. The suggested solution is an appropriate option for healthcare institutions since it offers a strong defense against a range of cyber threats, including targeted and espionage assaults.

Muhammad Kashif, Kübra Kalkan

No abstract is available for this record.

Yi Yu, Shuai Liu, Yi Huang, C. Y. Chung · 5 authors

With the ongoing development of renewable energy sources, information technologies and physical energy systems are further integrated, which leads to challenges in ensuring the secure and stable operation of renewable energy power systems in the face of potential cyber threats. The strengths of blockchain in cybersecurity make it a promising solution to these challenges. However, existing blockchains are not well-suited for control tasks due to their low real-time performance. Here, we present a consensus mechanism that enables real-time security control of systems, called Proof of Task. Instead of solving meaningless hash puzzles in Proof of Work, Proof of Task addresses problems closely related to the stable operation and control performance of these systems. With the proposed verification mechanism, Proof of Task significantly enhances the real-time performance of blockchain while mines its computational resources for tasks of interest. To demonstrate the effectiveness and necessity of Proof of Task, it is deployed across three renewable energy power systems. The results show that Proof of Task markedly fortifies the security and computing capability of these systems, ensuring their reliable and stable operation. This work highlights the promise of blockchain to facilitate security control and trusted computing of large-scale, complex-dynamic systems. For control systems, blockchain usually exhibits a trade-off between security and real-time performance. Here, authors propose a new mechanism that utilizes multi-party computation and verification with prediction, specifically tailored for real-time security control of renewable energy power systems.

Aruna Malik, Vikas Tyagi, Samayveer Singh, Rajeev Kumar · 6 authors

The advent of sixth-generation (6G) technology is poised to revolutionize connectivity, particularly by enhancing the integration of Internet of Medical Things (IoMT) devices. This advancement offers ultra-fast data transmission, low latency, and high mobility but also brings the challenge of ensuring secure and energy-efficient communication. To solve these challenges, this paper introduces a novel hybrid greylag goose-based optimized clustering (HGGOC) algorithm. It merges the efficiency of greylag goose optimization with the precision of the golden sine strategy. The Lévy flight mechanism guides the algorithm to optimize cluster head selection in 6G-enabled IoMT networks. The integration of blockchain technology further strengthens data security and transparency. Simulation results show that HGGOC surpasses existing methods, delivering up to 64% improvement in network stability, a 47% increase in node lifetime, and a 59% boost in energy efficiency and data throughput. These findings position HGGOC as a promising solution for sustainable communication in 6G-enabled IoMT environments.

Carlo Kleber da Silva Rodrigues

Aplicações computacionais de bases de dados distribuídas estão sempre presentes na sociedade digital. Uma importante questão é que essas bases de dados sejam seguras, auditáveis, transparentes e escaláveis. Este artigo possui dois objetivos: (i) prover um arcabouço teórico sobre Distributed Ledger Technologies (DLTs) para implementação de bases de dados distribuídas, e (ii) propor um método de seleção do tipo de plataforma DLT para uma organização alvo, denominado Método Ágil de Seleção (MAS). Para tanto, inicialmente realizamos um estudo de trabalhos da literatura e, na sequência, derivamos o MAS. Além disso, demonstramos a aplicabilidade do MAS por meio de um estudo de caso. Por fim, conclusões gerais e trabalhos futuros encerram este artigo.

Koya Haritha, Sai Srinivas Vellela, D Roja, Lakshma Reddy Vuyyuru · 6 authors

Blockchain and SDN are combined in the "DistB-SD Cloud" architecture to secure and execute cloud-integrated IoT data. Cloud Computing Management and Services, Distributed Secure Blockchain Methodology, SDN Environment, and Data Extraction comprise the architecture. SDN-enabled devices safely gather and process sensor data in the data plane, while OpenFlow and OpenStack handle network component communication in the control plane. The application layer improves network administration with dynamic configuration and data analytics. Distributed nodes and hash chains ensure system integrity in blockchain-based access control and ledger maintenance. Blockchain and SDN improve security, privacy, and scalability by resisting attacks. The architecture outperforms OpenFlow-based SDN models in throughput and bandwidth, proving its stability under different network conditions. The study shows that the suggested "DistB-SD Cloud" achieves increased throughput (22.1 KB/s) and bandwidth (1.9 GB/s) when nodes and packet arrival rates increase, making it a feasible solution for safe and scalable cloud computing in IoT-based systems.

Saurav Ghosh, Reshmi Mitra, Indranil Roy, Bidyut Gupta

Ensuring security for highly dynamic peer-to-peer (P2P) networks has always been a challenge, especially for services like online transactions and smart devices. These networks experience high churn rates, making it difficult to maintain appropriate access control. Traditional systems, particularly Role-Based Access Control (RBAC), often fail to meet the needs of a P2P environment. This paper presents a blockchain-based access control framework that uses Ethereum smart contracts to address these challenges. Our framework aims to close the gaps in existing access control systems by providing flexible, transparent, and decentralized security solutions. The proposed framework includes access control contracts (ACC) that manage access based on static and dynamic policies, a Judge Contract (JC) to handle misbehavior, and a Register Contract (RC) to record and manage the interactions between ACCs and JC. The security model combines impact and severity-based threat assessments using the CIA (Confidentiality, Integrity, Availability) and STRIDE principles, ensuring responses are tailored to different threat levels. This system not only stabilizes the fundamental issues of peer membership but also offers a scalable solution, particularly valuable in areas such as the Internet of Things (IoT) and Web 3.0 technologies.

Chaimae El Filali, Imad Bourian, Khalid Chougdali

The healthcare sector stands to benefit greatly from the integration of Internet of Things (IoT) technologies. IoT-based healthcare systemscan offer personalized care services without restrictions on time or location, enhancing patient well-being. However, ensuring robust data protection and security remains a significant challenge in IoT deployments. To address this, we propose an integrated solution that leverages Ethereum blockchain and Attribute-Based Access Control (ABAC) mechanism. This approach ensures the integrity and transparency of healthcare data, while providing fine-grained access controls. The sensitive data is encrypted using Advanced Encryption Standard (AES) and stored in a decentralized manner on the Interplanetary File System (IPFS). This enhances the overall security and privacy of the system. Furthermore, all transactions within the system are recorded on the blockchain, ensuring the traceability of the processes. Finally, we carry out experiments to assess the performance aspects of the proposed framework.

Liang Wang, Jianping Li, Lina Zuo

No abstract is available for this record.

Tripti Bhardwaj, Ujjval Jain, Rupinder Kaur, Shreyan Bharadwaj · 5 authors

This project presents a decentralized educational platform designed to enhance accessibility and transparency in online learning through blockchain technology. The platform operates on a unique model where courses are purchased as NFTs (Non-Fungible Tokens), allowing students to own a digital proof of enrollment while enabling educators to receive full compensation without third-party fees. By leveraging blockchain, the system provides secure, direct transactions and transparent records, mitigating common issues such as transaction delays and profit-sharing costs. The platform architecture is centered around user roles: students, educators, and administrators, each having designated functions to ensure seamless interaction. Blockchain development, frontend design, backend integration, and data management are key areas of focus, each managed by a specialized team member. Additionally, features like secure login, user-friendly interfaces, and responsive classroom access contribute to an intuitive and efficient user experience. This research demonstrates the potential of decentralized solutions in education, offering a cost- effective, accessible, and scalable model that aligns with the evolving demands of digital learning. The platform paves the way for future enhancements, including expanded course offerings and AI-driven personalized learning pathways.

Umar Draz, Tariq Ali, Sana Yasin, Mohammad Hijji · 6 authors

Wireless sensor networks deployed in energy-constrained environments face critical challenges relating to sustainability and protection. This paper introduces an innovative blockchain-powered safe energy-swapping protocol that enables sensor nodes to voluntarily and securely trade excess energy, optimizing usage and prolonging lifespan. Unlike traditional centralized management schemes, the proposed approach leverages blockchain technology to generate an open, immutable ledger for transactions, guaranteeing integrity, visibility, and resistance to manipulation. Employing smart contracts and a lightweight Proof-of-Stake consensus mechanism, computational and power costs are minimized, making it suitable for WSNs with limited assets. The system is built using NS-3 to simulate node behavior, energy usage, and network dynamics, while Python manages the blockchain architecture, cryptographic security, and trading algorithms. Sensor nodes checked their power levels and broadcast requests when energy fell under a predefined threshold. Neighboring nodes with surplus power responded with offers, and intelligent contracts facilitated secure exchanges recorded on the blockchain. The Proof-of-Stake-based consensus process ensured efficient and secure validation of transactions without the energy-intensive need for Proof-of-Work schemes. The simulation results indicated that the proposed approach reduces wastage and significantly boosts network resilience by allowing nodes to remain operational longer. A 20% increase in lifespan is observed compared to traditional methods while maintaining low communication overhead and ensuring secure, tamper-proof trading of energy. This solution provides a scalable, safe, and energy-efficient answer for next-generation WSNs, especially in applications like smart cities, precision agriculture, and environmental monitoring, where autonomy of energy is paramount.

Burhan Ul Islam Khan, Asadullah Shah, Khang Wen Goh, Rusnardi Rahmat Putra · 6 authors

This paper presents a pioneering analytical framework for a secure payment system leveraging blockchain technology tailored to regions with suboptimal network connectivity. Contemporary payment mechanisms utilizing Ethereum are predominantly optimized for areas with robust network infrastructure, neglecting regions with less connectivity. To address this gap, the proposed model integrates novel security attributes and employs an analytical method to design a decentralized payment system. The framework facilitates communication between low-connectivity zones and Internet service providers through auxiliary nodes, creating a local blockchain network for residents, merchants, and auditors. A mathematical model quantifies operational costs, transaction processing, and synchronization of auxiliary nodes, ensuring a resilient and secure payment architecture. A unique aspect of the proposed approach is its robustness against auditor outages and network variability, coupled with an empirical analysis of incentive structures for auditors' block validation activities. Moreover, it delineates the minimum requirements for secure transaction completion. Empirical findings showed a significant improvement in system efficiency, including a 79% reduction in block time, a 28% increase in transaction throughput, a 30% decrease in energy consumption, a 68% shorter confirmation time, a 63% reduction in execution time, a 46% increase in block production rate, and 82% reduced network variability. This study's significant contribution lies in introducing a sustainable, cost-effective, and secure payment system for regions with inadequate network services.