ABSTRACT The wide adoption of Internet of Things (IoT) devices has created an urgent need for secure, scalable data management solutions that can operate within the constraints of resource‐limited hardware. While blockchain technology offers compelling security through decentralisation, traditional consensus mechanisms like Proof‐of‐Work (PoW) are fundamentally incompatible with IoT environments due to excessive energy consumption and low throughput. This article introduces ECC‐PoARV, a novel blockchain architecture combining elliptic curve cryptography with proof‐of‐authority using rotational validation, designed specifically for the demands of modern IoT networks. Through a comprehensive simulation‐based evaluation of a 100‐node network, our architecture demonstrated a sustained throughput of 140 transactions per second (TPS) with a deterministic 0.05‐second finality time. These results represent a 14‐fold throughput improvement and a staggering >5000‐fold latency reduction compared to Proof‐of‐Work's (PoW) probabilistic finality of ∼283 s, all while consuming over 95% less energy per transaction. Critically, unlike standard Proof‐of‐Authority systems that can suffer from centralisation risks, our rotational validation mechanism ensures equitable validator participation and enhances fault tolerance. These findings establish Elliptic Curve Cryptography—Proof‐of‐Authority based on Rotational Validation (ECC‐PoARV) as a practically deployable solution that successfully bridges the performance gap between insecure centralised systems and computationally intensive blockchains, providing a viable blueprint for next‐generation IoT security.
ABSTRACT The management of electronic health records (EHR) demands not only secure storage but also rigorous access monitoring to safeguard patient privacy and ensure regulatory compliance. While blockchain technology provides data immutability, many healthcare systems lack integrated and effective auditing mechanisms, exposing them to risks of data breaches, unauthorised access, and compliance failures. This study proposes a blockchain‐enabled EHR access monitoring framework that incorporates advanced auditing tools to capture comprehensive metadata on access events, including who accessed the data, when, where, how, and why. To address the limitations of traditional purpose‐based access control, the framework integrates context‐aware access control and attribute‐based access control models. These enable dynamic, context‐sensitive, and attribute‐driven access policies based on parameters such as user role, time, location, and data sensitivity. Additionally, real‐time auditing capabilities are enhanced using Elasticsearch, Splunk, and Grafana for log analysis, anomaly detection, data visualisation, and predictive analytics. This integration not only strengthens surveillance but also enables timely responses to suspicious activities. By leveraging blockchain's tamper‐proof ledger and combining it with automated auditing and intelligent access control, the proposed framework enhances security, supports compliance with regulations like HIPAA (health insurance portability and accountability act) and GDPR(general data protection regulation), and fosters institutional trust through transparent and accountable data governance in healthcare environments.
ABSTRACT Efficient disaster response requires scalable, transparent and trustworthy resource management systems. However, centralized approaches frequently suffer from coordination delays, data tampering risks, limited transparency and single points of failure, reducing reliability during large‐scale crises. This study presents a decentralised blockchain‐based framework that integrates smart contracts, decentralised multi‐source oracles for Internet of Things (IoT)‐enabled field reporting, role‐based access control and adaptive urgency scoring to improve allocation prioritisation and trust calibration. The architecture follows a structured three‐tier design. The edge layer supports real‐time sensing and secure data offloading through the Inter‐Planetary File System (IPFS). The blockchain logic layer enforces operational policies, dynamic prioritisation, and reputation scoring using modular, gas‐efficient smart contracts. An integration/API layer ensures secure interoperability among emergency agencies and stakeholders. A hybrid blockchain model combines Ethereum Proof‐of‐Stake (PoS) for public transparency with a permissioned consortium chain for controlled governance. Natural Language Processing (NLP) derives urgency scores from textual disaster reports, while a dynamic supply‐demand aware algorithm adapts resource allocation in real time. Multi‐signature governance and reputation mechanisms further enhance accountability. Experimental evaluation on a simulated testnet demonstrates throughput up to 1000 Transactions Per Second (TPS), alongside measurable improvements in fairness, auditability and allocation efficiency.
ABSTRACT In centralized systems prone to data breaches and single points of failure, issues about security, privacy, scalability, and real‐time sharing of electronic health records (EHRs) have arisen in the context of healthcare digitization. To tackle these problems, this paper proposes blockEHR, a decentralized EHR sharing system that uses blockchain technology and protects users' privacy. To communicate health data securely in real time, the suggested method employs Internet of Medical Things (IoMT) devices, edge computing, and a permissioned private Ethereum blockchain. Data collected by IoMT sensors is confirmed at the edge by means of digital signatures, identity cross‐referencing, and GPS‐based verification. Data on blockchains is protected by smart contracts and access controls based on roles. Both AES‐256 encryption and SHA‐256 hashing ensure the security of the data. In real time, the system can handle 1850 records/second with minimal latency and great throughput, according to the experiments. The findings demonstrate that blockEHR maintains patient privacy and allows practical healthcare applications while being a secure, scalable and effective decentralized method for managing electronic health records.
ABSTRACT Blockchain systems rely on stable network connectivity to ensure secure and tamper‐proof transactions. While this works well in areas with reliable network connectivity, it can limit blockchain's functionality in remote areas or during natural disasters. Over the years, blockchain‐based digital currencies have gained popularity as a means of payment. In order for digital currencies to be comparable with physical cash, blockchain systems need to adopt and support offline transactions. To address these issues, researchers are exploring the potential of offline blockchain systems. In this paper, we provide a systematic study on offline blockchain implementations. We present the various security and privacy issues that arise from the absence of network connectivity in blockchain systems. To better understand the offline blockchain implementations, we provide a systematic and novel categorisation of the various methodologies and analyse how different combinations of methods are used together. Additionally, we outline a three‐phase framework that systematically maps security risks to each execution phase of offline blockchain systems. Furthermore, a comparative analysis of the literature based on the security and privacy issues addressed is provided, and a discussion on the research gaps and the current state of offline blockchain systems is summarised.
ABSTRACT With the advent of blockchain technology, the need to employ third parties, known as oracles, to assist smart contracts has become clear. Blockchain smart contracts can only operate on on‐chain data and face the major challenge of not being able to communicate with the outside world. Blockchain oracles resolve this problem by bridging the gap between on‐chain and off‐chain data. Oracles can exhibit inappropriate behaviours or selfishly hide their true resources to maximise profits. Current research presents oracles as trusted entities without providing a robust evaluation mechanism for them. This type of design carries the risk of turning oracles into central points of failure. In this paper, a new approach inspired by reinforcement learning (Q‐learning) is proposed. We investigate the performance of oracles and select reliable and cost‐effective oracles from the blockchain network and compare the efficiency of the proposed method with previous well‐known methods. This method, which we call IPQL ‘Integer‐based pseudo‐Q‐Learning’, helps to identify reliable and cost‐effective oracles more effectively. The proposed model analyses the behaviour of oracles using a performance‐cost table and a framework inspired by the Q‐learning algorithm. The IPQL model allows all blockchain validators to verify the results obtained during the execution of the algorithm, thus addressing the issue of randomness in the limited structure of the blockchain. Finally, IPQL is compared with current state‐of‐the‐art methods based on accuracy, cost, and execution time. The results show that the proposed method leads to a 31% increase in success rate and 10% request redirection to safe oracles, a 22% reduction in request redirection to malicious oracles, and a 9.1% improvement in time.
ABSTRACT Objective: The markets of cryptocurrencies are highly volatile, and the trading is constant, which makes it especially difficult to predict the prices correctly. The majority of current prediction methods are mostly based on historical data and do not remain applicable in real‐time. In this work, the authors provide a proposal of CryptoCastAI , a two‐pipeline artificial intelligence‐based cryptocurrency forecasting model, which can be used to complement the practical application and decision support by incorporating both the analysis of the historical data and the analysis of the market (in real time). Method: The suggested framework includes the use of three complementary forecasting models: Prophet that allows modelling interpretable trends and seasonality, XGBoost that allows modelling nonlinear price dynamics, and Long Short‐Term Memory (LSTM) networks that allow sequential learning of temporal patterns. Historical price data of Bitcoin and Ethereum were used to analyse the model performance, and the performance of real‐time data was evaluated using the live market data, which were obtained via the CoinGecko Application Programming Interface (API). Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE) and coefficient of determination ( R 2 ) were used to assess model performance. The system was implemented through an interactive system in Streamlit that allowed visualising predictions, volatility, and performance of the models in real‐time. Result: The experimental findings on the static historical data show that XGBoost was the best model with an MAE of 140.72, RMSE of 266.52, MAPE of 7.30%, and an R 2 of 0.46, which has a higher predictive accuracy than other models. Prophet had a good trend and seasonality interpretation but lower predictive performance (MAE = 243.75, RMSE = 415.26, R 2 = −0.49). LSTM performed the worst in the static environment (MAE = 363.39, RMSE = 443.70, R 2 = −0.12) and had weaknesses in forecasting real‐time as it is sensitive to short‐term market fluctuations. Conclusion: The results indicate that the combination of multiple forecasting machine learning algorithms in a single, real‐time framework can improve predictive power as well as interpretability in cryptocurrency price forecasting. The CryptoCastAI is a good solution to the problem of implementing academic forecasting models in the real world by providing a combination of live data ingestion, model comparison, and user‐friendly visualisation. The suggested system can be a scalable and interpretable decision‐support system to analyse cryptocurrency markets in real‐time and emphasise the feasible benefits of ensemble‐based AI forecasting strategies.
ABSTRACT As climate change intensifies, reliable product carbon footprint accounting requires not only accurate calculation but also auditable multi‐party data management. This study presents a system design and prototype validation of a blockchain‐based product carbon footprint accounting system. The system combines a standard life cycle assessment (LCA) pipeline with a permissioned blockchain, smart‐contract‐based rule execution and auditable on‐chain records. The contribution is an engineering integration and validation framework rather than a new blockchain consensus algorithm. Using 1200 lifecycle records from three product categories, eight enterprises and four regions, we evaluate accounting error, processing efficiency, consistency and tamper evidence under controlled deployment (12 PBFT nodes). Compared with the manual LCA workflow, the prototype improves accounting efficiency by 76.39%, keeps calculation deviations within ±5% (MAPE 2.08%) and reaches 98.5% cross‐regional record consistency. Additional comparisons with non‐blockchain digital baselines show that blockchain mainly improves multi‐party auditability and post‐submission data integrity. The results support prototype‐level feasibility, while source‐data truthfulness and large‐scale‐node performance remain open challenges.
ABSTRACT With the rapid development of the internet of things (IoT), the security collaboration between devices poses higher demands on traditional trust management. Blockchain technology, due to its decentralisation and tamper‐proof characteristics, has become an effective solution for building trustworthy IoT systems. However, traditional consensus protocols (like PBFT) face issues such as high communication overhead and insufficient scalability in IoT environments. In response, an improved consensus protocol, Improved Practical Byzantine Fault Tolerance (IPBFT), is proposed, which combines K‐means to optimise node grouping, reducing network communication complexity, while also introducing a dynamic credit assessment mechanism to evaluate the trustworthiness of nodes and filter reliable consensus nodes. Finally, based on these two improvements, a trust system for IoT based on Hyperledger Fabric is designed and implemented. Experimental results show that compared to traditional PBFT, IPBFT reduces latency and communication complexity by over 50%, making it more suitable for large‐scale IoT trust management scenarios and providing a new technical approach for efficient and trustworthy collaboration in blockchain applications within the IoT.
ABSTRACT The proliferation of Internet of Things (IoT) devices has created an urgent demand for secure, scalable and interoperable data‐sharing architectures. Centralized paradigms exhibit single points of failure, inadequate access control and limited transparency, rendering them structurally misaligned with the distributed nature of IoT deployments. This paper presents a systematic review and taxonomy of blockchain‐based secure data‐sharing frameworks for IoT, synthesizing 20 peer‐reviewed studies published between 2019 and 2025. The literature is organized into four thematic clusters: (i) access control and authentication, (ii) decentralized storage and integrity verification using IPFS, (iii) privacy‐preserving federated learning integrated with blockchain and (iv) domain‐specific deployments in healthcare, industrial IoT, and intelligent transport systems. For each cluster, we synthesize consensus mechanism choices, chain‐type selection, storage strategy, access‐control model and threat‐model coverage.
ABSTRACT Traditional energy markets are hindered by centralization, high transaction costs, and the systemic exclusion of small‐scale prosumers. While blockchain‐based peer‐to‐peer (P2P) energy trading platforms offer a decentralized alternative, most suffer from scalability bottlenecks, volatile transaction fees, and poor regulatory alignment—limiting real‐world deployment. To bridge this gap, we propose decentralized energy management system (DEMS): a decentralized energy management system built on a permissioned Hyperledger Besu network with IBFT 2.0 consensus, ERC‐20‐compliant ENRTokens, and a hybrid Web2/Web3 authentication layer. DEMS enables secure, transparent, and regulation‐aware P2P energy trading within positive energy districts (PEDs). Evaluated on a 4‐node consortium and scaled to 50 nodes via Hyperledger Caliper, the system achieves 5–7 transactions per second (TPS) with sub‐2‐second finality and predictable operational costs. Unlike public Ethereum or DAG‐based alternatives, DEMS supports complex smart contract logic while ensuring GDPR‐compliant data handling, role‐based access control and auditability. This work contributes a novel, regulation‐oriented architecture that integrates energy tokenization with real‐world policy constraints, laying the groundwork for scalable, AI‐enhanced decentralized energy markets.
ABSTRACT In Zambia, we do not have a foolproof system that can help in tracking drugs from the manufacturers through the supply chain to the consumers in real time. This paper highlights how we solved this problem through the use of blockchain technology. Blockchain technology provides a distributed record of transactions (ledger) that allows transactions to be written efficiently and permanently. Further, it provides a mechanism for verifying such transactions. The developed solution, the Medicine Tracking System (MTS), uses a public blockchain architecture that works on a Proof of Work (PoW) consensus algorithm. The MTS keeps a record of all the major transactions that occur between the manufacturer and the end‐user of the medicine. A transaction can be a sale, a receipt of medicine, a delivery, an issuance of a prescription or even a report of damage. Each transaction is input into the system by the main player or actor at each occurrence of the transaction, keeping note of the details such as the date and location of the transaction. By tracking these details about a transaction, it was possible to trace with certainty and accuracy the path that a particular medicine traversed to the end‐user and all the actors involved along the way. Therefore, any unauthorised actors were easily identified and dealt with. Further, the quality of the medicine was monitored and kept in check. Because each transaction is time‐sensitive, the duration of medicines in transit or storage was measured concerning their expiry date. The PoW consensus algorithm was used to achieve agreement or consensus on every transaction sent to the network. Multiple nodes participated in validating a transaction, and these had to reach consensus by following the mechanisms provided for by this algorithm. This was achieved by creating a unique timestamp for each transaction and then packaging it into a block. The contents of the block were then hashed using PoW and added to the chain with a pointer to the preceding block's hash through a process called mining. To successfully mine a block, a miner has to compute the solution to a mathematical problem. The mined block then has to be broadcast to the network. This created a record of transactions that could not be altered unless the PoW was redone. The results of the system show that users in the pharmaceutical chain can record transactions they are involved in. Furthermore, the system can transmit all transactions to the blockchain, where miners can capture them, verify them, and add them to the blockchain database, forming an indelible record of transactions. Unlike existing blockchain‐based pharmaceutical systems such as MediLedger, PharmaLedger, and Blockpharma, which primarily focus on regulatory integration within high‐income countries, our MTS is specifically designed for the Zambian pharmaceutical ecosystem, which lacks the necessary infrastructure and connectivity to adopt existing global models. The novelty of MTS lies in its context‐aware implementation, which combines blockchain transparency with localised mobile interfaces, lightweight nodes, and integration with the Zambia Medicines Regulatory Authority framework. This localised adaptation demonstrates how blockchain can be operationalised in low‐resource and semi‐decentralised environments, providing a scalable, verifiable, and regulatory‐compliant model for medicine traceability in developing countries.
ABSTRACT Although blockchain technology offers a promising solution for issuing secure and verifiable academic micro‐credentials (MCs), its widespread adoption in academic institutions faces scalability limitations. This scalability issue creates a significant bottleneck, as traditional one‐credential‐per‐transaction models become economically unviable for organisations that need to issue thousands of credentials simultaneously. However, effective solutions for mass issuance remain to be explored. To address this gap, this study proposes an approach, implements it and evaluates a novel framework that integrates batching strategies with Merkle trees and off‐chain storage using the interplanetary file system (IPFS). The experimental evaluation was conducted on Sepolia (Ethereum test network) using metrics such as gas usage, throughput and execution time. The experimental results showed stable gas consumption at approximately 90,487 units, throughput improvements from 0.31–13.77 transactions per second (TPS) and consistent execution times of approximately 32 s. This study contributes a scalable and economically viable system architecture that decouples credential metadata from its on‐chain proof, providing a clear pathway for institutions to adopt blockchain technology for large‐scale credential management and advancing the practical implementation of verifiable digital credentials in education.
ABSTRACT Bidding transactions are widely used in scenarios such as government procurement and corporate tendering. However, while traditional blockchain achieves transparency in transactions, it also poses a risk of sensitive information such as bidder identity, quotation, and time being leaked, thereby undermining the fairness and compliance of bidding. Addressing the challenge of the incompatibility between strong anonymity and regulatory compliance in existing blockchain privacy protection schemes, this paper proposes a blockchain bidding privacy protection scheme with threshold traceability based on the bidding transaction scenario. Firstly, our scheme constructs a permissioned ring signature structure based on qualification verification, achieving strong identity anonymity while ensuring the validity of anonymous aggregation. By introducing a time‐lock commitment mechanism and a zero‐knowledge timeliness verification mechanism, it ensures the confidentiality of bidding content while guaranteeing that the submission is completed before the deadline, thereby achieving verifiable temporal compliance. To balance privacy protection and regulatory compliance, this paper designs a (t, n) threshold traceability mechanism based on Shamir's secret sharing, which fragments the master key among multiple regulators. Only through multi‐party collaborative authorisation can the identity of non‐compliant bidders be revealed, thereby reducing the risk of regulatory abuse. Security analysis proves that this scheme meets security requirements such as unforgeability, bidding privacy, and policy integrity under standard cryptographic assumptions. Extensive experimental results indicate that the proposed scheme achieves competitive performance in terms of privacy preservation and traceability compared with existing schemes.
ABSTRACT Indonesia has established itself as a regional leader in cryptocurrency adoption; however, its regulatory framework is marked by institutional fragmentation and patchwork legal mandates. The introduction of a widely accepted Rupiah‐pegged stablecoin could provide a locally governed digital currency that fosters financial innovation while mitigating reliance on foreign‐denominated assets. In this study, we propose a policy‐driven architecture that emphasizes transparency through a three‐layer model for the issuance, reservation and circulation of stablecoins. Community visibility into the status of the Rupiah stablecoin can be achieved by implementing a system across three publicly accessible decentralized ledgers, each dedicated to managing different aspects of the stablecoin lifecycle. The proposed three‐layer model addresses the current gap between policy and implementation, offering policymakers and regulators relevant ‘policy hooks’ into the technological layer that enacts policies. Furthermore, the three‐layer model facilitates a shared techno‐regulatory framework for policymakers, regulators, technology providers and entrepreneurs to consider the various operational aspects of Rupiah stablecoins.
ABSTRACT The promise of blockchain applications is transformative in terms of certificate verification and managing digital identities in the various fields, such as education, healthcare and land records. Nevertheless, current blockchain‐based certificate solutions have serious shortcomings: most are based on simple cryptography protection with no privacy‐preserving systems, have low throughput (16.67 TPS in typical Ethereum‐based systems), have unpredictable response times under varying loads, are not standardised across industries and are expensive to operate due to gas fees. Besides, the current implementations are mostly either theoretical or without performance tests in practice. This paper fills these gaps by suggesting a Plonk‐based system that incorporates zero‐knowledge proofs, digital signatures and trusted identity verification to improve the efficiency, security, and privacy of the verifiable credential digital identity verification and management systems (VC DIVMS). It was implemented at JIS University, India, with 50 transactions per minute (an improvement of 200% over Ethereum), an error rate of 244–1277ms in response times under load conditions (24‐33 faster than Ethereum) and high‐level privacy through ZKP. Contrary to currently used models that are sector‐specific, the offered Plonk framework offers a single, scalable, privacy‐focused model that can be applied in areas of education, healthcare, or credit verification. Intense testing ensured both resilience, scalability and compatibility with a demanding environment, making Plonk a strong and secure substitute to decentralised identity verification and credential management that is resistant to tampering.
In the current Internet era, whether the domain name system (DNS) can achieve efficient resolution is of great significance for optimizing user experience and promoting global development. However, the existing DNS architectures have flaws in dealing with network service latency and ensuring their own robustness. Based on this, this study constructs a blockchain-based distributed domain master architecture, aiming to optimize the resolution effect of top-level domains (TLDs). As internet service latency continues to pose severe challenges to user experience and global development, the demand for accelerated DNS resolution always exists. Although local caching has always been helpful in improving DNS efficiency, how to ensure the integrity of cached records is a tricky problem. The new architecture proposed in this study adopts a consortium blockchain framework, allowing nodes to freely enter and exit. Consensus is reached through the 3R-PBFT algorithm, strengthening system security. Focusing on the top-level domains of.com and.net, an in-depth exploration is conducted on the effect of locally deployed caches on resolution time, highlighting the key value of TLD caches in enhancing the DNS resolution speed. Experimental results show that the local cache implemented through the consortium blockchain architecture can not only improve the security of the cache but also reduce the latency of DNS resolution.
The distributed denial of service (DDoS) attacks represent a real danger on cloud computing systems, the existing security approaches have notable limitations such as centralization, lack of adaptability and scalability, and focusing on detection over mitigation. In this paper, we present a novel blockchain-based system to enhance attack tolerance of cloud systems against DDoS attacks by integrating a hierarchical risk-based cloud attack tolerance mechanism with smart contracts, The proposed approach ensures comprehensive threat detection and mitigation by estimating risks at all three layers: local, cluster, and global dynamically using Dempster–Shafer theory. Simulations validated the superiority of our approach compared to similar systems in terms of availability, attack detection rate, and packet loss metrics in large-scale cloud simulation of 10,000 nodes. The results demonstrate that our system not only improves security but also maintains service quality under high-intensity attack scenarios. Additionally, the implementation of our blockchain architecture shows significant scalability and cost-efficiency, thus, confirming its suitability for large cloud deployments. Furthermore, the reliability of the smart contracts against potential threats were confirmed by a formal security analysis using the Echidna tool.
