Mohammad Yaser Mofatteh, Ujjwal Khadka, Omid Fatahi Valilai
Energy management can be designed from different perspectives including production, distribution, and consumption. Focusing on consumption perspective, manufacturing systems can be enhanced by enabling smart machines as agents which operate with their own knowledge representation models in a shopfloor. These agents can benefit from industry 4.0 enablers like IoT including sensors, controllers, and actuators. This paper focuses on how these agents can interoperate with each other and exchange knowledge to optimize energy consumption. Since different knowledge models may not be capable of interacting with other ones based on their different provider semantics. This paper explores the application of blockchain technology for secure, decentralized storage and sharing knowledge models in smart energy systems. The research introduces EnerChain as a blockchain-integrated and a decentralized application (DApp) system prototype that employs smart contracts for access management and conflict resolution. It also incorporates the InterPlanetary File System (IPFS) for efficient off-chain storage, addressing scalability concerns. The feasibility and practicality of this approach are demonstrated through the development of EnerChain. The findings highlight the significant potential of blockchain technology in facilitating efficient knowledge model management for smart shopfloors. Additionally, an operational scenario has been evaluated as a case study for the proposed conceptual model to illustrate how it can solve energy conflicts in a smart environment. An impact analysis at the end of this research shows that EnerChain can make annual 27.5 TWh reduction in residential energy consumption which yields to annual 7.8 million tonnes reduction in CO 2 emissions and annual €8.25 billion financial benefits.
Abstract Applying Distributed Ledger Technologies to securely manage intercommunicated data between IoT applications has recently been adopted on an enormous scale. They enable data integrity, privacy, and robustness to public, open, permission-less P2P networks. Voting-based consensus algorithms proved high efficiency even with limited computing and less power IoT devices. Moreover, they can identify legitimate information and isolate malicious attackers through repetitive voting queries to adjacent peers asking their opinions about the validity of each transaction. Several lightweight validation models are introduced to enrich IoT networks with better performance and higher security. Nevertheless, the current algorithms struggle to find adequate parameters that balance network security and operability, in addition to balancing fairness in distributed environments. This paper introduces an Autonomous Lightweight Ledger Constructor to resolve common defects and threats. Based on Reinforcement Learning, it can dynamically construct a valid distributed ledger in limited-computing systems under several adversarial conditions. The validity of transactions in this approach is calculated based on their cumulative weights and the issuer’s reputation, which are inferred subjectively by a lightweight Bayesian-like function. A new simulator is developed to evaluate ALLC performance and security. The experimental results demonstrate reasonable performance and high resistance against known compromises targeting Distributed Ledger Technologies.
Ensuring scalability in cryptocurrency systems is significant in guaranteeing real-world utility along with the remarkable increment of cryptographic currency. As an alternative in solving scalability issue, payment channel allows users to deliver extensive offline transactions without uploading massive transaction details to the blockchain, such that increasing efficiency can be achieved. However, the implementation of payment channel still encounters privacy concerns when considering the publicly available transaction amounts and the potentials in mining associations between transaction parties. In this paper, we propose a novel payment channel scheme, entitledCommitment-basedAnonymousPayment ChannEl (CAPE), to facilitate unlimited off-chain bidirectional payments while guaranteeing participants’ privacy. The proposed scheme adopts zero-knowledge proof (zk-SNARKs) and verifiable timed (VTD) commitments to ensure the anonymity of the relationship between on-chain and off-chain transactions, privacy of transaction amounts, and security of balances. We comprehensively formalize security definitions and present rigorous proofs for each security attribute. Experiment results further demonstrate the practical viability of CAPE.
Digital product passports (DPPs) will become a reality for several regulated products in Europe. The topic is still in its infancy but will significantly impact product information and the infrastructure required by manufacturing in increasingly agile and circular supply chains. This paper presents the results of a two-year design science research to develop an end-to-end blockchain-based DPP prototype instantiated in the textile industry. On the one hand, the upstream supply chain involves physical product transformations from the early stages of production, requiring a robust traceability architecture. On the other hand, multiple events occur during downstream phases that need to be easily accessible by different stakeholders. Our results confirm the suitability of blockchain-based DPPs and define the information flow within the product life cycle. This paper advances the literature on sustainable product identification, ensuring tamper-proof and transparent information in the supply chain. Although aiming at the end consumers, the DPP will majorly impact production, requiring proper industry planning. For practitioners, this paper provides one of the first DPP instantiations in different segments of the textile supply chain, highlighting the requirements that the industry should be aware of for the coming years. Eleven design principles for blockchain-based DPPs are proposed.
Future generations of wireless networks at high-frequency spectrum suffer from limited coverage and Non-Line- of-Sight signal blockage, challenging emerging applications, such as smart industries and intelligent automation systems. Collaborative and cooperative communications with smart relays via Non-Orthogonal Multiple Access (NOMA) could be a breakthrough solution to this challenge. This paper presents a blockchain-integrated framework for NOMA wireless communication systems that incentivizes cooperation among users serving as relays. By leveraging Ethereum-based smart contracts, we introduce a Service Verification Contract featuring a Proof of Quality of Experience (PQoE) mechanism. The contract uses trust scores, weighted verifications, and dynamic validation thresholds to ensure honest behavior and deter malicious activities. The simulation results show that honest participants gradually increase their trust scores and require fewer verifications, while malicious verifiers lose influence over repeated rounds. Our findings indicate that combining trust-based incentives with a decentralized ledger can effectively promote reliable data-relaying services and streamline payment processes in collaborative and smart wireless networking systems.
Ensuring data integrity is crucial for IoT-based healthcare and emotion care services, which utilize Fog computing to bring resources and services closer to the network edge. This proximity, however, increases the risks of data tampering, loss, and unauthorized access. To mitigate these risks, Distributed Ledger Technology (DLT) platforms such as Hash graph, Big chain-DB, IOTA (Internet of Things Application) and Blockchain are being investigated for their potential to enhance data integrity within Fog computing environments. This study presents a framework designed to ensure data integrity in IoT-based healthcare and emotion care services by leveraging IOTA technology. IOTA, which employs a directed a-cyclic graph (DAG) structure known as the Tangle, provides a secure, decentralised and tamper-resistant method for data storage and sharing. Unlike traditional blockchain, IOTA’s consensus mechanism operates without miners, offering improved scalability and efficiency suitable for IoT environments. Our proposed framework exploits IOTA’s capabilities to deliver a robust solution for maintaining data integrity in Fog computing contexts. The evaluation results demonstrate the framework’s feasibility and effectiveness in enhancing data integrity for IoT-based healthcare and emotion care services. Although IOTA significantly improves data integrity by complicating unauthorized data alterations, it is essential to acknowledge that complete immutability is influenced by various factors, such as consensus mechanisms and the number of network participants, similar to the limitations observed in other DLTs. • Integrating Fog Computing with Distributed Ledger Technology (DLT) utilizing IOTA. • Leveraging the “Immutable Data Tangle” structure to safeguard data against unauthorized modifications and tampering. • Fortifying Resilience against Security Threats using DLT (IOTA). • Provides insights into the effectiveness of hybrid cryptanalytic attacks and the role of DLT (IOTA) integration in countering them. • Practical implementations are meticulously presented, accompanied by real-world case studies.
Introduction The insurance industry has evolved into a global multi-billion-dollar sector, with health insurance gaining prominence due to escalating healthcare costs. This rapid expansion brings heightened risks, including data breaches, fraud, and difficulties in safeguarding sensitive policyholder information. Indonesia’s National Health Insurance (NHI)—one of the largest national insurance programs worldwide—covers over 200 million citizens, aiming to provide universal healthcare. However, this extensive coverage raises substantial concerns about data privacy and traceability, particularly during the claim process, as policyholders currently have limited control over and insight into how their data is accessed and used. Methods To address these challenges, we propose a blockchain-based model designed to enhance policyholders’ private control over data access and improve traceability throughout the NHI claim process. Our approach employs three complementary architectures—functional, logical, and physical—to guide system implementation. The functional architecture is illustrated via a use case diagram that outlines the roles and actions of each participant. The logical architecture employs Business Process Model and Notation (BPMN) diagrams to depict the revised process flow and data movement, while also incorporating a layered design concept. The physical data architecture provides a class diagram detailing data structures and actor relationships. A proof-of-concept prototype was developed to demonstrate the core functionalities of the new system. Results By integrating blockchain technology, our prototype ensures authorized access, bolsters data privacy, and maintains data integrity in the NHI claim workflow. The system’s layered design and use of smart contracts guarantee transparent, tamper-proof record-keeping, while parallelized processes in the logical architecture streamline claims handling. Initial tests of the prototype confirm the feasibility and robustness of the proposed solution, illustrating how blockchain can facilitate traceability and preserve confidentiality. Discussion The blockchain-based design addresses pressing concerns surrounding data security and accountability in large-scale health insurance systems. It allows policyholders to monitor and control their personal information, reducing the likelihood of unauthorized use. Furthermore, the transparent and immutable ledger enables stakeholders to verify data provenance and transactions, enhancing trust. Future work will focus on scalability, regulatory compliance, and integration with existing healthcare IT infrastructures to fully realize the benefits of blockchain in national health insurance programs.
The rapid growth of IoT has increased the demand for large-scale data processing. However, traditional centralized methods struggle with real-time requirements and data security . This paper introduces VCD-TSNet, a novel real-time IoT data processing framework that combines blockchain and edge computing . By integrating deep learning models like VGG, ConvLSTM , and DNN , VCD-TSNet effectively performs spatial feature extraction, temporal modeling , and decision-making, while using blockchain to ensure data integrity and privacy. Experimental results demonstrate that VCD-TSNet outperforms baseline models in classification accuracy , prediction precision, and real-time performance. For instance, on the BoT-IoT dataset, the classification accuracy reaches 97.5%, throughput increases to 920 TPS, and response time stays below 85 ms. This study validates the model’s effectiveness and highlights its potential in large-scale IoT environments, offering efficient, secure solutions for real-time data processing. It also provides insights for future improvements in frameworks that combine edge computing with blockchain.
Web3 is the next-generation internet, utilizing blockchain technology to power decentralized applications and give users greater control. However, the scalability limitations of blockchain create performance bottlenecks that hinder Web3’s overall processing capabilities. Among current scalability solutions, multi-chain architecture has been considered a promising approach with high flexibility. However, current multi-chain architecture lacks portability to existing blockchains and relies on relayers to solve timing issues in the interoperability process. The lack of portability makes it challenging for existing blockchains to adopt the current multi-chain architecture, significantly impeding multi-chain promotion. Moreover, relying on relayers to address timing issues leads to low efficiency and potential reliability risks. This paper introduces Zunesha, a multi-chain architecture that designs a smart-contractbased multi-chain toolkit (STACK) to provide a portable multi-chain architecture. Additionally, it introduces the Dynasty-Based Consensus Node Set Verification (DB-CNSV) protocol as a foundational safety mechanism to eliminate relayers in the interoperability process and address timing issues. Our evaluation shows that Zunesha significantly enhances the overall performance of the blockchain. As the number of subchains increases, the throughput grows almost linearly. Furthermore, the performance of inter-chain transactions surpasses that of the current mainstream multi-chain architecture, Cosmos.
Damilare Peter Oyinloye, Je Sen Teh, Mohd Najwadi Yusoff
Blockchain technology has been adopted in various sectors including health, energy and agriculture. It functions as a distributed ledger maintained by multiple nodes, relying on consensus protocols to verify transactions and reach agreement. However, conventional protocols like Proof of Work (PoW) and Proof of Stake (PoS) face challenges with scalability and energy efficiency. This paper introduces Proof of Collaborative Contribution (PoCC), a new consensus protocol aimed at encouraging positive network contributions and fostering collaboration. It utilizes a simplified hashing mechanism secured by trusted execution environments (TEEs). As a proof of concept, PoCC is applied to a solar energy generation system, where prosumers are incentivized to offset their energy consumption and feed excess energy back into the grid. Using real-world energy data from AusGrid, our simulations demonstrate that PoCC ensures equitable block leader selection. We also show that PoCC scales well with the number of nodes, consumes significantly less energy than PoW, and is resistant to Sybil and 51% attacks. We also briefly explore other potential applications of PoCC in systems that aim to reward node contributions.
This article presents a novel framework for implementing decentralized identity management in microservices architecture using blockchain technology. The proposed solution addresses the inherent challenges of traditional centralized identity management systems by leveraging distributed ledger technology and smart contracts to create a secure, transparent, and user-centric authentication mechanism. The framework incorporates comprehensive privacy controls and consent management features while ensuring compliance with regulatory requirements across various industries. Through extensive evaluation across multiple use cases in healthcare, financial services, and government sectors, the results demonstrate enhanced security, improved scalability, and better user privacy control compared to conventional approaches. The article suggests that blockchain-based identity management can significantly reduce the risk of security breaches while providing a more robust and flexible authentication mechanism for modern distributed systems. This article contributes to the growing body of knowledge in distributed systems security and provides practical insights for organizations looking to implement decentralized identity management solutions.
As the acceptance of Internet of Things (IoT) systems quickens, guaranteeing their sustainability and reliability poses an important challenge. Faults in IoT systems can result in resource inefficiency, high energy consumption, reduced security, and operational downtime, obstructing sustainability goals. Thus, blockchain (BC) technology, known for its decentralized and distributed characteristics, can offer significant solutions in IoT networks. BC technology provides several benefits, such as traceability, immutability, confidentiality, tamper proofing, data integrity, and privacy, without utilizing a third party. Recently, several consensus algorithms, including ripple, proof of stake (PoS), proof of work (PoW), and practical Byzantine fault tolerance (PBFT), have been developed to enhance BC efficiency. Combining fault detection algorithms and BC technology can result in a more reliable and secure IoT environment. Thus, this study presents a sustainable BC-Driven Edge Verification with a Consensus Approach-enabled Optimal Deep Learning (BCEVCA-ODL) approach for fault recognition in sustainable IoT environments. The proposed BCEVCA-ODL technique incorporates the merits of the BC, IoT, and DL techniques to enhance IoT networks’ security, trustworthiness, and efficacy. IoT devices have a substantial level of decentralized decision-making capacity in BC technology to achieve a consensus on the accomplishment of intrablock transactions. A stacked sparse autoencoder (SSAE) model is employed to detect faults in IoT networks. Lastly, the Piranha Foraging Optimization Algorithm (PFOA) approach is used for optimum hyperparameter tuning of the SSAE approach, which assists in enhancing the fault recognition rate. A wide range of simulations was accomplished to highlight the efficacy of the BCEVCA-ODL technique. The BCEVCA-ODL technique achieved a superior FDA value of 100% at a fault probability of 0.00, outperforming the other evaluated methods. The proposed work highlights the significance of embedding sustainability into IoT systems, underlining how advanced fault detection can provide environmental and operational benefits. The experimental outcomes pave the way for greener IoT technologies that support global sustainability initiatives.
Nabil A. Ismail, Shaimaa Abu Khadra, Gamal Attiya, Salah Eldin S. E. Abdulrahman
Abstract Blockchain technology offers a robust framework for integration with the Internet of Things (IoT), enhancing interoperability, security, privacy, and scalability in modern technological ecosystems. However, traditional cryptographic protocols used in blockchain systems are increasingly vulnerable to quantum attacks due to advancements in quantum computing. In response, the National Institute of Standards and Technology (NIST) has prioritized research in post-quantum cryptography, presenting challenges and opportunities for developing blockchain-based applications tailored to IoT devices. Among the post-quantum cryptographic schemes evaluated in NIST's third standardization round, the Supersingular Isogeny Key Encapsulation (SIKE) protocol stands out for its relatively small public and private key sizes. Despite this advantage, SIKE faces challenges related to high latency, necessitating efficient implementations to make it viable for real-world applications. This research focuses on optimizing the cryptographic foundations of blockchain networks to securely and efficiently integrate resource-constrained IoT ecosystems. By enhancing the SIKE protocol, which exhibits strong resistance to brute-force and whitewashing attacks, the study achieves significant performance improvements. Our FPGA-based implementation on the VIRTEX-6 XC6VLX760 demonstrates reduced latency, achieving a key generation time of 24 ms, encapsulation time of 72 ms, and decapsulation time of 73 ms for SIKEp434. These results highlight the feasibility of deploying SIKE-optimized blockchain networks in IoT environments with stringent resource constraints.
As healthcare systems increasingly adopt fog computing to improve responsiveness and real-time data processing at the edge, significant security challenges emerge due to the decentralized architecture. The traditional perimeter-based security models are inadequate for addressing the dynamic and distributed nature of fog networks, leaving them vulnerable to unauthorized access, data tampering, and latency issues. Therefore, this paper proposes a novel security framework that integrates blockchain (BC) and software-defined network (SDN) technologies, underpinned by zero-trust (ZT) principles, to address these challenges in latency-sensitive healthcare environments. The proposed framework enhances security by combining BC’s immutable transaction logs for data integrity and traceability with SDN’s dynamic network reconfiguration for real-time access control and anomaly detection. The integration of BC and SDN supports continuous authentication and monitoring using cryptographic protocols (SHA-256A and RSA-2048) to secure data transmission. Additionally, tasks are dynamically allocated to fog nodes based on a multi-metric scheduling mechanism that considers fog node capacity, proximity, and compliance with predefined security protocols. The framework was evaluated using iFogSim, simulating a healthcare environment with 50 IoT devices, 10 fog nodes, and varying workloads (100–1000 tasks/min). The key evaluation performance metrics include intrusion detection rate (IDR), data integrity (DI), task completion rate (TCR), average task response time (ART), and average block time. The implementation results demonstrate satisfactory improvements compared to existing models: a 40% increase in IDR, a 30% enhancement in DI, a 15.29% rise in TCR, and a 39.66% reduction in ART. Moreover, the baseline IDR (85%) and DI (70%) were drawn from ZT-1, while TCR (85%) and ART (300 ms) were measured using ZT-2 as benchmarks. These findings illustrate the feasibility of integrating BC, SDN, and ZT principles to mitigate threats such as unauthorized access, data tampering, and delays in latency-sensitive tasks.
M. Natarajan, A. Bharathi, C. Sai Varun, Shitharth Selvarajan
Nowadays, most of the medical records are maintained in a digital format known as Electronic Health Records Sharing (EHRS) framework. Patients have individual login credentials for accessing these medical records. In the BCT, the information about the owner of the block and its dependency over other blocks is maintained in itself. Moreover, each block is linked with its nearby blocks, leading to a network controlled by patients responsible for storing and sharing the information. In healthcare, BCT can help with mobile health apps, monitoring equipment, sharing and keeping of clinical trial data, electronic medical records, and insurance information storage. This study proposes a secure Patient Login Credential System (PLCS) for EHRS. The proposed scheme has been included for block encryption with the symmetric and asymmetric cryptography algorithms with respect to the hospital server and patients. Additionally, the Quantum Secure Trust Protocol (QSTP) is integrated to enhance trust and security between the patient-side and hospital-side, maintaining data integrity and confidentiality. Similarly, the Tune Swarm Optimization (TSO) algorithm is utilized to optimize performance metrics. The security analysis for the proposed scheme has been evaluated with basic security assumptions for information systems like, availability, access control, maintaining forward secrecy, and maintaining data integrity. The proposed scheme demonstrated enhanced security and performance, with IDEA achieving encryption in 58 ms and decryption in 278 ms for a 512-bit block, offering the best performance in terms of encryption speed.
As IoT continues to expand, the security of connected devices remains a critical concern, particularly in the face of DDoS attacks. This study introduces a novel approach that leverages blockchain technology through smart contracts integrated with an advanced attack detection mechanism. Central to this approach is the Enhanced Residual Gated Recurrent Unit (ERGRU) architecture, designed to effectively identify and mitigate DDoS attacks within IoT networks. The Adaptive Coati Optimization Algorithm (ACOA) was used to adjust the hyperparameters of the ERGRU model, such as the learning rate and the number of GRU neurons, to further improve detection accuracy. In addition, the proposed framework uses a one-way compression function to generate secure hashes for input data, utilizing the Merkle-Damgård cryptography technique to ensure data integrity and confidentiality. The proposed solution was tested through a rigorous process using a DDoS dataset. Performance was assessed by focusing on metrics such as processing time, data integrity rate, and confidentially rate. The results demonstrate the effectiveness of the proposed smart contract-based framework in providing a durable and efficient protection mechanism against DDoS attacks in IoT environments.
With the further expansion of 5G networks, a main priority continues to shift towards secure and efficient protocols for data transmission. Traditional 5G security mechanisms, such as 3GPP AKA protocols, have limitations in scalability, latency, and resilience against cyber threats, making them quite unsuitable for complex high-density 5G environments. This study proposes a Secure Blockchain-based Data Transmission Protocol (SBDTP) with the decentralized and tamper-resistant feature of blockchain, combined with a hybrid consensus mechanism driven by Proof of Stake (PoS) or Practical Byzantine Fault Tolerance (PBFT). In this respect, this study contributes to state-of-the-art research efforts in the field of enhancing data integrity, authentication, and confidentiality with reduced latency and energy consumption in 5G applications. Extensive simulations showed that SBDTP outperformed previous solutions by a large margin. This protocol reduces latency to 50-80 ms, increases throughput to 900 pps, allows up to 1000 nodes without performance degradation, and reduces energy consumption to 0.8 J per node. It also maintains a very close-to-perfection data integrity check rate of ~100% and a very minimal privacy loss rate of less than 1%, showing strong security that could serve well for real-time 5G applications such as IoT networks, autonomous vehicles, and smart cities. These results show that SBDTP offers an efficient and secure solution for data transmission over 5G networks, outperforming traditional and blockchain-based methods while fulfilling the tight requirements posed by next-generation networks. In the future, the protocol should be optimized for scalability, including further advanced privacy techniques to widen its adaptability to diverse 5G applications.
Scalability and automation in “Industrial Internet of Things (IIoT)” aims to improve productivity in smart factory setting. For scalability, protection, collaboration, optimization, and automation in industry, smart systems, Internet of Things (IoT), and information and communication technologies (ICTs) are integrated as an individual organism. This study proposes a safe data-sharing system based on blockchain to provide security in industry with IoT. As per blockchain’s reputation, end-to-end authentication is developed and smart contract can validate security measures of nodes. With categorization and integrity verification in industry and node terminals, the paradigm of blockchain manages dissemination and data collection. The “Proof of Authentication (PoAh)” is a consensus mechanism developed with blockchain network to develop a collaborative network for retaining verification and log data in IIoT. It achieves tracing of endpoint activity and trusted authentication. Blockchain nodes also uses edge computing to provide authentication of devices using PoAh and smart contracts. The proposed architecture achieves high response rate and cuts the time for authentication. The service time in the proposed system shows efficiency of blockchain system for IIoT in comparison to current works. Finally, several block sizes were evaluated for efficient transaction.
Juan Minango, Henry Carvajal Mora, Marcelo Zambrano, Nathaly Orozco Garzón · 5 authors
This paper evaluates the technical feasibility of Distributed Ledger Technology (DLT) within the healthcare ecosystem, with a focus on the use of Corda DLT to enhance governance and performance in a decentralized ecosystem, ensuring data integrity, security, and trustworthiness. Key attributes examined include the guarantee of data integrity, ensuring that transmitted data remain unaltered; authenticity through the implementation of digital signatures and certificates; confidentiality achieved via secure peer-to-peer communication accessible only to authorized parties; and traceability and auditing mechanisms that enable tracking of information changes and accountability. To validate these features, a Corda Distributed Application (CorDapp) was developed to manage the core logic of the healthcare ecosystem. The CorDapp was deployed across nodes and executed within the Corda network. Its performance was assessed using metrics such as throughput, latency, CPU usage, and memory consumption in both local and cloud network environments. Results demonstrate the feasibility of using Corda DLT technology in healthcare, effectively addressing critical requirements such as integrity, authenticity, confidentiality, traceability, and auditing while maintaining satisfactory performance across diverse deployment scenarios.
Aiming to address the shortcomings of traditional blockchain technologies, characterized by high storage redundancy and low transaction query efficiency, we propose a lightweight sender-based blockchain architecture (LSB). In this architecture, the linkage between blocks is associated with the user initiating the transaction, and the hash of the newly generated block is recorded in the user’s wallet, thereby facilitating transaction retrieval. Each user node must store only the blocks that pertain to it, significantly reducing storage costs. To ensure the normal operation of the system, the Delegated Proof of Stake based on Reputation and PBFT (RP-DPoS) consensus algorithm is employed, establishing a reputation model to select honest and reliable nodes for consensus participation while utilizing the Practical Byzantine Fault Tolerance (PBFT) algorithm to verify blocks. The experimental results demonstrate that LSB reduces storage overhead while enhancing the efficiency of querying and verifying transactions. Moreover, in terms of security, it decreases the likelihood of malicious nodes being designated as agent nodes, thereby increasing the chances of honest nodes being selected for consensus participation.
The proliferation of Internet of Things (IoT) devices in smart environments has created unprecedented challenges in identity management and security. Traditional centralized identity management systems face scalability, privacy, and single-point-of-failure issues when applied to IoT ecosystems. This paper presents a novel blockchain-based framework for decentralized identity management in smart IoT environments. Our proposed framework leverages blockchain technology's immutable ledger, smart contracts, and cryptographic mechanisms to provide secure, scalable, and privacy-preserving identity management for IoT devices. The framework incorporates a multi-layered security architecture that includes device authentication, access control, and identity verification mechanisms. Experimental results demonstrate that our approach achieves 99.7% authentication accuracy with reduced latency compared to traditional centralized systems. The framework also provides enhanced privacy protection through zero-knowledge proofs and selective disclosure mechanisms. This research contributes to the advancement of secure IoT identity management and provides a foundation for future developments in decentralized IoT security
Manufacturing sectors pursuing Industry 5.0 objectives increasingly require automation architectures capable of reasoning across heterogeneous cyber-physical domains while advancing sustainability targets. This paper synthesizes evidence from eighteen references spanning semantic web technologies, cyber-physical systems, digital twins, blockchain-enabled traceability, and multi-agent reinforcement learning to propose a Semantic AI-Orchestrated Cross-Domain Automation Framework for sustainable smart factories. The framework integrates a five-layer architecture, comprising physical sensing, cyber-physical integration, semantic reasoning, cross-domain orchestration, and sustainability decision layers, into a unified reasoning pipeline in which ontology-driven knowledge graphs mediate interoperability among heterogeneous equipment, enterprise systems, and human operators. Comparative synthesis indicates that semantic-based autonomous computing architectures reduce unplanned downtime by as much as 37 percent, while multi-agent reinforcement learning scheduling raises resource utilization to 88 percent relative to 58 percent under conventional rule-based scheduling. Interoperability standards such as OPC-UA demonstrate adoption rates near 78 percent among reviewed implementations, and hybrid semantic-blockchain ledgers achieve transaction throughput exceeding 2,100 transactions per second at latencies below 40 seconds, outperforming public proof-of-work ledgers by more than two orders of magnitude. Digital twin adoption trajectories synthesized from the references rose from approximately 8 percent in 2016 to 66 percent by 2024, correlating with a 24 percent reduction in energy consumption and a 31 percent reduction in material waste across reviewed sustainable manufacturing cases. The findings imply that semantic orchestration, combined with decentralized ledgers and human-centric digital twins, offers a scalable pathway toward resilient, low-carbon, and economically viable smart factory operations, while highlighting persistent challenges in ontology standardization, explainability, and cross-organizational governance.
Qi An, Frank Jiang, Chengzu Dong, Shantanu Pal · 7 authors
The rapid expansion of electric vehicle (EV) infrastructure necessitates advanced solutions for secure and private authentication at EV charging stations. This research introduces a blockchain-based framework enhanced with self-sovereign identity (SSI) features, targeting the improvement of privacy and security in cyber marketplaces for EVs. The inclusion of SSI enables users to maintain full control over their digital identities, a critical advancement for authentication processes at EV charging stations. This system effectively addresses the growing privacy and security challenges within the expanding EV infrastructure. By integrating Zero-knowledge proof with self-sovereign identity, the framework not only ensures robust security but also preserves user privacy by enabling users to prove their identity without exposing sensitive personal information. We propose an efficient and user-friendly solution, showcasing its potential as a pioneering innovation in the field of EV charging infrastructure.
Nik Nor Muhammad Saifudin Nik Mohd Kamal, Safwah Afiqah, Sara Khadeja, Aliya Nasuha · 9 authors
Ethereum and Hyperledger are two popular and well-known block chain platforms which represent two kinds of application differentiation. Ethereum is a decentralized platform that also allows DApps to operate on it; many of the conditions for performing functions on Ethereum’s blockchain do not require permission to be granted, but smart contracts are available. On the other hand, the Hyperledger Fabric, an enterprise grade blockchain solution, provides the permission to access, update, and apply scalability, privatization, and mandatory access control mechanisms. Due to the decentralized nature and the capacity of performing smart contracts using Ethereum Virtual Machine (EVM), it has been used in a number of areas across the world in financial transactions and DApp. Hyperledger fabric, on the other hand, is pursuant to the permissioned network standards and is centred on providing the set of components that suffice the requirement of an enterprise thereby making it easier for the organization to build a blockchain, which is both highly scalable and security conscious. Some of the studies have researched on Ethereum as well as Hyperledger Fabric in a variety of contexts as depicted by the following: From these studies, it explains how blockchain has the potential in increasing volume in various areas while enhancing its characteristics such as, openness, origin and audibility. Analysing the concrete features of the Ethereum and Hyperledger Fabric platforms, it is almost obligatory for the companies interested into the implementation of the blockchain technology to understand the possibilities offered by one system and the drawbacks some complexity or singularity of the other. That is why, the features of each platform are distinctive and could be utilized for the development of business processes in specific spheres when designing problem-solving approaches.