Blockchain Framework Research Articles

Towards quantum‐safe blockchain: Exploration of PQC and public‐key recovery on embedded systems

AbstractBlockchain technology ensures accountability, transparency, and redundancy, but its reliance on public‐key cryptography makes it vulnerable to quantum computing threats. This article addresses the urgent need for quantum‐safe blockchain solutions by integrating post‐quantum cryptography (PQC) into blockchain frameworks. Utilizing algorithms from the NIST PQC standardization process, it is aimed to fortify blockchain security and resilience, particularly for IoT and embedded systems. Despite the importance of PQC, its implementation in blockchain systems tailored for embedded environments remains underexplored. A quantum‐secure blockchain architecture is proposed, evaluating various PQC primitives and optimizing transaction sizes through techniques such as public‐key recovery for Falcon, achieving up to 17% reduction in transaction size. The analysis identifies Falcon‐512 as the most suitable algorithm for quantum‐secure blockchains in computer‐based environments and XMSS as a viable but unsatisfactory stateful alternative. However, for embedded‐based blockchains, Dilithium demonstrates a higher transactions‐per‐second (TPS) rate compared to Falcon, primarily due to Falcon's slower signing performance on ARM CPUs. This highlights the signing time as a critical limiting factor within embedded blockchains. Additionally, smart contract functionality is integrated, assessing the impact of PQC on smart contract authentication. The findings demonstrate the feasibility and practicality, paving the way for robust and future‐proof IoT applications.

Enhancing Smart Grid Security Using BLS Privacy Blockchain With Siamese Bi‐LSTM for Electricity Theft Detection

ABSTRACTEnergy management inside a blockchain framework developed for smart grids is primarily concerned with improving intrusion detection to protect data privacy. The emphasis is on real‐time detection of cyberattacks and preemptive forecasting of possible risks, especially in the realm of electricity theft within smart grid systems. Existing Electricity Theft Detection techniques for smart grids have obstacles such as class imbalance, which leads to poor generalization, increased complexity due to large EC data aspects, and a high false positive rate in supervised models, resulting in incorrect classification of regular customers as abnormal. To provide security in the smart grid, a novel BLS Privacy Blockchain with Siamese Bi‐LSTM is proposed. Initially, the privacy‐preserving Boneh‐Lynn‐Shacham blockchain technique is built on BLS Short signature and hash algorithms, which mitigate misclassification rates and false positives in the detection of smart grid attacks. Then, a hybrid framework employs an intrusion detection algorithm based on Siamese Bidirectional Long Short‐Term Memory to semantically distinguish between harmful and authentic behaviors, thereby improving data quality and predictive capabilities. Furthermore, a Recurrent Neural Network‐Generative Adversarial Network is presented for detecting electricity fraud, which addresses the issue of class imbalance. This uses both supervised and unsupervised loss functions to produce synthetic theft samples that closely resemble actual theft incidents. From the experiment, it is showing that the proposed models perform with high accuracy and low error rates. The proposed model from the outcomes when compared to other existing models achieves high accuracy, detection rate, recall, and low computation time.

Implementing zero-knowledge proof authentication on Hyperledger fabric to enhance patient privacy and access control

In recent years, the healthcare sector has encountered significant challenges in authenticating identities for online medical services. A predominant reliance on centralized identity management systems (IDMs) has presented obstacles to the seamless exchange of patient identities among various healthcare institutions, often resulting in data isolation within individual silos. Of paramount concern are the potential privacy breaches associated with centralized IDMs, which may compromise patient confidentiality. In response to these challenges, we propose a novel approach to securely sharing patient details across multiple hospitals utilizing the zero-knowledge access protocol (MediCrypt-ZKAP) within the Hyperledger Fabric blockchain framework. By adopting MediCrypt-ZKAP, hospitals can effectively verify the identities of requesting entities without disclosing sensitive patient information, thereby ensuring the highest levels of confidentiality and privacy protection. The proposed system represents a proactive step towards addressing the critical need for secure and interoperable patient data exchange within the healthcare sector. Through the integration of MediCrypt-ZKAP into existing blockchain infrastructure, our solution aims to enhance data security and privacy while promoting seamless collaboration among healthcare institutions.

Optimizing demand response and load balancing in smart EV charging networks using AI integrated blockchain framework

Optimizing demand response and load balancing in smart EV charging networks using AI integrated blockchain framework

Fostering Transparency and Trust in Digital Advertising Through a Unified Blockchain Framework

The digital advertising sector is plagued by fraud, opacity, and inefficiency, eroding stakeholder trust and economic outcomes. Despite advances in digital marketing technologies, significant gaps remain in combating fraudulent activities and ensuring transparency. Addressing these challenges, this article proposes the AdChain framework, leveraging blockchain technology to revolutionise digital advertising by fostering transparency, reducing fraud, and enhancing operational efficiency. AdChain reconfigures the advertising landscape through a blockchain-based solution that ensures the authenticity and verifiability of ad engagements. By utilising blockchain’s intrinsic attributes, such as decentralisation, immutability, and transparency, AdChain aims to streamline digital advertising practices and restore trust among stakeholders. Using a qualitative approach, the study delineates the AdChain framework’s architecture, emphasising its decentralised nature, immutable records, and transparent processes. These features are designed to mitigate the prevalent issues in digital advertising, providing a more secure and efficient environment for all participants. Our findings indicate that AdChain effectively addresses advertising fraud and enhances the consumer experience by prioritising privacy and data control. This results in substantial economic benefits, optimising advertisers’ return on investment (ROI) and increasing publishers’ revenues. However, realising AdChain’s full potential requires overcoming several obstacles, including technical challenges related to scalability and system integration. Additionally, barriers to widespread adoption, such as regulatory uncertainties and the necessity for industry collaboration and standardisation, must be addressed. Despite these challenges, AdChain presents a promising avenue for transforming digital advertising, offering a robust solution to longstanding issues and paving the way for a more transparent and efficient advertising ecosystem.

A secure and efficient blockchain enabled federated Q-learning model for vehicular Ad-hoc networks

Vehicular Ad-hoc Networks (VANETs) are growing into more desirable targets for malicious individuals due to the quick rise in the number of automated vehicles around the roadside. Secure data transfer is necessary for VANETs to preserve the integrity of the entire network. Federated learning (FL) is often suggested as a safe technique for exchanging data among VANETs, however, its capacity to protect private information is constrained. This research proposes an extra level of security to Federated Q-learning by merging Blockchain technology with VANETs. Initially, traffic data is encrypted utilizing the Extended Elliptic Curve Cryptography (EX-ECC) technique to enhance the security of data. Then, the Federated Q-learning model trains the data and ensures higher privacy protection. Moreover, interplanetary file system (IPFS) technology allows Blockchain storage to improve the security of VANETs information. Additionally, the validation process of the proposed Blockchain framework is performed by utilizing a Delegated Practical Byzantine Fault Tolerance (DPBFT) based consensus algorithm. The proposed approach to federated Q-learning offered by Blockchain technology has the potential to develop VANET safety and performance. Comprehensive simulation tests are performed with several assessment criteria considered for number of vehicles 100, Throughput (102465.8 KB/s), Communication overhead (360.57 Mb), Average Latency (864.425 ms), Communication Time (19.51 s), Encryption time (0.98 ms), Decryption time (1.97 ms), Consensus delay (50 ms) and Validation delay (1.68 ms), respectively. As a result, the proposed approach performs significantly better than the existing approaches.

The realization of the “Concept of digital transformation, development of the information and communication technologies and cybersecurity industry for 2023‒2029” by implementing blockchain in the technologies of the Republic of Kazakhstan and the prob

In the scientific article, the implementation of the “Concept of digital transformation, development of the information and communication technologies and cybersecurity industry for 2023‒2029” was considered, which, according to the authors, is possible through the prism of the introduction of blockchain technologies in the Republic of Kazakhstan. The main focus is on analyzing the current state of the digital infrastructure, identifying potential applications of the blockchain and identifying regulatory issues related to its use. The article begins with an overview of the strategic objectives of the Concept and an assessment of its impact on the economic development of the country. The authors discuss blockchain as an innovative tool capable of ensuring transparency, security and reliability of data in various sectors, including finance, healthcare and public administration. In this aspect, an overview of existing technologies that have already been applied in practice was conducted; accordingly, the Republic of Kazakhstan can adopt them for the future. Special attention is paid to the analysis of the problems faced by Kazakhstan in integrating blockchain technologies into the existing legal system. The authors explore the need to develop new legislative acts, as well as adapt existing regulatory documents to create a favorable legal environment for blockchain. The potential risks and benefits that may arise as a result of the large-scale introduction of blockchain technologies in Kazakhstan are also discussed. In conclusion, the article offers recommendations on improving the legal framework for blockchain, emphasizing the importance of international cooperation and exchange of experience in this area.

Correction to: SHBF: a secure and scalable hybrid blockchain framework for resolving trilemma challenges

Correction to: SHBF: a secure and scalable hybrid blockchain framework for resolving trilemma challenges

Unleashing the Potential of Permissioned Blockchain: Addressing Privacy, Security, and Interoperability Concerns in Healthcare Data Management

Blockchain technology leverages a cryptographic system to provide secure and immutable storage of transaction histories within a decentralised framework. While various industries have demonstrated interest in integrating blockchain into their IT systems, concerns regarding accessibility, privacy, performance, and scalability persist. Permissioned blockchain frameworks offer a viable solution for securing confidential records. Extensive research has been conducted to explore the opportunities, challenges, application areas, and performance evaluations of different public and permissioned blockchain platforms. Given the sensitive nature of medical information, healthcare organisations must adhere to various legal obligations, including HIPAA regulations, to protect these data. Although navigating these requirements can be challenging, it is crucial for safeguarding the reputation of healthcare providers, maintaining patient trust, and avoiding legal repercussions. Permissioned blockchains represent decentralised digital ledgers tailored to collaborate among businesses and organisations. Their popularity has increased significantly in recent years, resulting in the availability of several leading options, such as Hyperledger Fabric, Corda, Quorum, and MultiChain. Each of these platforms presents its own set of advantages and disadvantages. Although blockchain technology remains relatively nascent in the permissioned realm, several factors warrant consideration when comparing these platforms. This study will review the existing landscape of blockchain technologies in healthcare applications and identify the research scopes. This research aims to determine how permissioned blockchain technology can effectively fulfil the requirements for managing healthcare data.

Blockchain and Internet of Things Technologies for Food Traceability in Olive Oil Supply Chains.

This study presents a blockchain-based traceability system designed specifically for the olive oil supply chain, addressing key challenges in transparency, quality assurance, and fraud prevention. The system integrates Internet of Things (IoT) technology with a decentralized blockchain framework to provide real-time monitoring of critical quality metrics. A practical web application, linked to the Ethereum blockchain, enables stakeholders to track each stage of the supply chain via tamper-proof records. Key functionalities include smart contracts that automate quality checks, ensuring data integrity and providing immediate verification of product authenticity. Initial user feedback highlights the system's potential to enhance transparency and reduce fraud risks in the olive oil market, supporting consumer trust and regulatory compliance. This approach offers a scalable solution adaptable to other high-value agricultural products, demonstrating the blockchain's transformative potential for secure and transparent food traceability.

MLPhishChain: a machine learning-based blockchain framework for reducing phishing threats

MLPhishChain: a machine learning-based blockchain framework for reducing phishing threats

Blockchain Framework for Examination Result Processing System for a Kenyan University

Blockchain Framework for Examination Result Processing System for a Kenyan University

Integration and Optimization of Route Planning and Inventory Management in Supply Chain Transaction Systems: A Comprehensive Analysis

This comprehensive article analysis explores the integration and optimization of route planning and inventory management within supply chain transaction systems, examining their transformative impact across various industries. The article investigates the evolution of modern logistics operations, emphasizing the crucial role of advanced technologies, blockchain frameworks, and integrated systems in enhancing operational efficiency. Through a detailed examination of core components including algorithmic foundations, real-time tracking systems, demand forecasting mechanisms, and unified data architectures, this article presents a holistic view of contemporary supply chain optimization. The article analysis encompasses multiple sectors, including retail, e-commerce, and manufacturing, demonstrating how integrated systems have revolutionized traditional approaches to inventory management and route optimization. By exploring performance metrics, return on investment, and future trends, this article provides valuable insights into the implementation strategies and scalability considerations essential for modern supply chain systems. The article highlights the significance of cross-functional optimization and cloud-based solutions in achieving operational excellence while maintaining high levels of customer satisfaction and cost efficiency.

Smart Contract Powered Framework for the Next Generation Industry 4.0 Business Model

Blockchain stands as a crucial technology capable of enhancing transparency, security, and efficiency within various sectors. Particularly in Industry 4.0, blockchains can be employed to monitor the movement of goods and materials across the supply chain, ensuring data integrity, transparency, immutability, accountability, and industrial process interoperability. Industry 4.0 companies must interact with various external players, which often requires collaborations and partnerships to access new technologies, shared data and analytics, and required resources for their processes. However, current business process management in the industry is mostly centralized, untraceable, unreliable and lacks automation. Smart contracts hold the potential to tackle these concerns by offering a remarkable level of automation, transparency, and security while also aiding in regulatory compliance. However, the adoption of smart contracts in Industry 4.0 is still limited due to various obstacles. The challenges facing the deployment of Distributed Ledger Technology (DLT) in Industry 4.0 are multifaceted, encompassing issues such as interoperability across different blockchain systems, scalability and performance constraints, limitations on ensuring data privacy, difficulties in accessing external data sources, and the significant transaction costs often associated with executing smart contracts. To tackle these obstacles comprehensively, we advocate for the development of an interoperable consortium blockchain framework tailored to meet the versatile business processes required by Industry 4.0 enterprises or groups. This proposed architecture, distinct from any specific internal system, incorporates private channels and ensures secure access to external data, thus addressing broader interoperability concerns beyond just smart contracts. Our goal is to establish a comprehensive DLT framework that assures data integrity and traceability throughout its lifecycle, from creation and processing to its final utilization for business insights. The effectiveness of our approach is demonstrated through its application in a real-world industrial scenario, undertaken in partnership with Fagor Automation, a global leader in the industrial sector.

An enhanced deep learning integrated blockchain framework for securing industrial IoT

An enhanced deep learning integrated blockchain framework for securing industrial IoT

The application of blockchain technology to improve tax compliance and ensure transparency in global transactions

The digital transformation of global commerce has fundamentally altered the landscape of tax administration, presenting unprecedented challenges for tax authorities worldwide. This comprehensive review examines the transformative potential of blockchain technology in revolutionizing tax compliance and enhancing transparency in global transactions. Through systematic analysis of existing literature, case studies, and implementation frameworks, we investigate how blockchain's core attributes of immutability, traceability, and decentralization can address critical challenges in contemporary tax administration. The review synthesizes evidence from multiple jurisdictions, demonstrating blockchain's capacity to reduce tax fraud, streamline compliance processes, and facilitate real time tax collection. Our analysis reveals that blockchain implementation in tax systems can potentially reduce tax gaps by 75-80% in VAT schemes and decrease compliance costs by 40-50% for businesses operating across multiple jurisdictions. The paper also explores critical challenges, including scalability issues, regulatory frameworks, and implementation barriers, providing a balanced perspective on both opportunities and limitations. Furthermore, we examine emerging trends in blockchain based tax solutions, including smart contracts for automated compliance, cross border information sharing protocols, and real time reporting frameworks. This review contributes to the growing body of literature on digital transformation in tax administration by offering a comprehensive framework for understanding blockchain's role in creating more efficient, transparent, and equitable tax systems. Our findings suggest that while blockchain technology presents promising solutions for tax administration challenges, successful implementation requires careful consideration of technical infrastructure, legal frameworks, and international cooperation mechanisms.

A novel integration of Web 3.0 with hybrid chaotic-hippo-optimized Blockchain framework for healthcare 4.0

HealthCare 4.0 stands as a cutting-edge technology that integrates human-sourced data with communication systems to enable highly accurate clinical diagnostics and treatments. While sensor-based devices have simplified many aspects of daily life, these advancements also face significant security challenges, particularly in safeguarding patient information. In response, this research introduces a novel blockchain-based hybrid chaotic encryption and authentication for maintaining EHR transmissions aimed at robust and secure authentication within HealthCare 4.0. The complete framework incorporates the Infura Web API, using Python 3.19. To strengthen authentication security, modified Hippopotamus-evoked scroll maps are used to generate dynamic hashes in the genesis block formation, securing all EHR data in the proposed architecture. This entire framework was evaluated on the Ethereum Blockchain, leveraging Web 3.0, with Python 3.19 serving as the core programming environment for interface development. Security analysis was performed utilizing Burrows-Abadi-Needham (BAN) logic, while the framework's resilience was rigorously tested against NIST standards. Comparative testing highlights the model's superior defense capabilities against various attacks, surpassing other frameworks in complexity and robustness. The findings ultimately provide a comprehensive view of the optimized encryption scheme on blockchain technology and the future pathways for secure authentication frameworks in HealthCare 4.0.

PHR-NFT: Decentralized Blockchain Framework with Hyperledger and NFTs for Secure and Transparent Patient Health Records

Blockchain technology holds significant promise for healthcare by enhancing the security and integrity of patient health records (PHRs) through decentralized storage and transparent access. However, it has substantial limitations, including problems with scalability, high transaction costs, privacy concerns, and intricate stakeholder access management. This study presents PHR-NFT, a novel framework that strengthens PHR privacy by utilizing Hyperledger Fabric and non-fungible tokens (NFTs) to address these issues. PHR-NFT improves privacy and communication by letting patients keep control of their medical records while permitting temporary, permission-based access by medical professionals. PHR-NFT offers a transparent solution that increases trust among healthcare stakeholders through the robust and decentralized architecture of the Hyperledger Fabric. This study demonstrates the viability and effectiveness of the PHR-NFT framework through performance evaluations focused on transaction latency, throughput, and security. This research has valuable implications for enhancing data privacy and security in healthcare practices and insightful information about blockchain-based healthcare systems.

An Analytical Study on the Efficacy of Blockchain Frameworks for Student Grievance Management

An Analytical Study on the Efficacy of Blockchain Frameworks for Student Grievance Management

Secured Blockchain framework using deep learning to reduce the service latency in a 5G based distributed networking environment

The Internet of Things (IoT), which is also represented as Internet of Health Things (IoHT), has witnessed numerous progresses in recent existences, particularly in the management of healthcare-related data. Because those healthcare statistics ensure greater accuracy, security with improvedreliability, and higher data feature, supplying those data to those healthcare apps is a time-consuming difficulty this organisation is facing. To developstatisticsestablishing, data must be more secure and privacy-protected, as deep learning and privacy policies are enabled with 5G network. If the information is private, the information owner may be able to learn about it. The data process flow associated with IoHT is now connected to a variety of IoT devices as edge nodes, thanks to recent advancements. Learning at the nodes is more difficult because of the issue of a missing or insufficient amount of training data, which necessitates a completely distributed setting, as well as new, better datasets, their establishing, and their security. In this work, a Hy-FL-based Blockchain strategy is proposed since it is enabled with blockchain, which maintains trust ability and skilled data based on deep learning with enhanced validation. With the help of the suggested method, training information on the deep nodes can be encrypted and aggregated. In the analysis, data management is managed securely based on IoHT in terms of projected value, energy usage, and data correctness.