T Buvaneswari, Mageshkumar Naarayanasamy Varadarajan, M. Mythily, Hemantha Kumar B N · 8 authors
The swift expansion of the Internet of Things (IoT) has expedited the implementation of smart sensors, generating substantial volumes of time-series data that require safe, efficient, and dependable management. Current centralized systems have constraints in maintaining integrity, protecting communications, and deriving economic value from this data. A blockchain-based smart house gateway network is suggested to address security concerns in smart home environments. The framework has three layers: device, gateway, and cloud. Blockchain technology is integrated at the gateway layer to provide decentralized storage and safe data interchange, eliminating single points of failure inherent in centralized systems. This integration ensures authentication, high availability, and secure communication across devices and stakeholders. The system utilizes Ethereum blockchain technology and is assessed based on important parameters such as response speed and detection accuracy. Experimental study demonstrates that the framework much surpasses traditional methods, improving resilience and reliability in smart home IoT ecosystems. The suggested system offers a scalable approach for safe data management and dependable value exchange in dispersed settings.
Hafsteinn Hjartarson, Fjölnir Thrastarson, Anna Sigríður Íslind, Gísli Hjálmtýsson
Abstract Permissioned blockchains have gained prominence as a means of decentralizing trust while retaining controlled access, particularly in enterprise settings and regulated peer-to-peer environments. These systems offer advantages in scalability, performance, and security; however, challenges persist in effectively managing membership and its interaction with consensus protocols. Ethereum’s transition to Proof-of-Stake has also been a transition to managed membership, where validators are actively monitored and penalized for non-performance. This paper examines the dynamic tension between membership management and consensus protocols in permissioned blockchains, as well as the benefits of active management in improving overall system performance. In this paper, we propose a framework for dynamic membership management that includes actively admitting, monitoring, and ejecting members. Our approach decouples membership management from the underlying blockchain construction process. Our simulations confirm the potential benefits of managed membership, in part to facilitate lightweight mechanisms for improved performance and reliability. Our findings suggest that dynamic membership management is a critical area of study with significant implications for the future design of permissioned blockchains. Our contributions provide a conceptual foundation for designing dynamic membership protocols in permissioned blockchains, filling a gap in the literature and offering practical solutions to enhance blockchain performance in controlled environments.
Rahanatu Suleiman, Akshita Maradapu Vera Venkata Sai, Wei Yu, Chenyu Wang
Digital Twins (DTs) have become essential tools for improving efficiency, security, and decision-making across various industries. DTs enable deeper insight and more informed decision-making through the creation of virtual replicas of physical entities. However, they face privacy and security risks due to their real-time connectivity, making them vulnerable to cyber attacks. These attacks can lead to data breaches, disrupt operations, and cause communication delays, undermining system reliability. To address these risks, integrating advanced security frameworks such as blockchain technology offers a promising solution. Blockchains’ decentralized, tamper-resistant architecture enhances data integrity, transparency, and trust in DT environments. This paper examines security vulnerabilities associated with DTs and explores blockchain-based solutions to mitigate these challenges. A case study is presented involving how blockchain-based DTs can facilitate secure, decentralized data sharing between autonomous connected vehicles and traffic infrastructure. This integration supports real-time vehicle tracking, collision avoidance, and optimized traffic flow through secure data exchange between the DTs of vehicles and traffic lights. The study also reviews performance metrics for evaluating blockchain and DT systems and outlines future research directions. By highlighting the collaboration between blockchain and DTs, the paper proposes a pathway towards building more resilient, secure, and intelligent digital ecosystems for critical applications.
The rise of Non-Fungible Tokens (NFTs) and Internet of Things (IoT) devices created new demands for secure data management. To address these needs, we propose LIBLO, a lightweight blockchain-based smart NFT architecture designed for decentralized environments with limited resources. Traditional models mostly depend on heavy computation techniques to ensure the data security. To avoid this, LIBLO introduces a compressed blockchain layer combined with lightweight encryption techniques. This allows secure storage, verification, and controlled access to IoT-generated data without overloading devices. In this architecture, LIBLO acts as a trusted digital framework that securely encapsulates metadata, ownership identity, and access control policies. Each transaction is verified through digital signatures and efficiently recorded on a compressed blockchain ledger. This design ensures privacy, traceability, and integrity and also contributes to energy-efficient implementation in real-time IoT scenarios. Experimental results demonstrate that the suggested LIBLO achieves high encryption strength and strong decryption accuracy of 0.96%, and low error rates of (1.1%). By simplifying cryptographic operations and reducing blockchain complexities, LIBLO presents a practical and adaptable solution for securing digital assets and IoT interactions in smart environments.
The rapid development of the Internet of Things (IoT) has intensified security and privacy challenges across data generation, transmission, and storage. This study introduces a blockchain-based secure edge storage model tailored for IoT environments and presents a lightweight consensus algorithm, Deep Q-Network (DQN)-Raft+, which incorporates deep reinforcement learning. By combining the decentralized features of edge computing and blockchain, the model enables automated data access control through smart contracts. Furthermore, it optimizes leader node selection in the Raft consensus process using a DQN, formulating the consensus as a Markov Decision Process to enhance responsiveness and privacy protection in dynamic network conditions. Experiments were performed in a simulated environment using TensorFlow 2.6 and a MySQL database. The performance of DQN-Raft+ was compared against traditional consensus algorithms, including Proof of Work, Proof of Stake, Practical Byzantine Fault Tolerance, and Delegated Byzantine Fault Tolerance. Results indicate that DQN-Raft+ significantly reduces block generation delay (175.77 ms) and achieves a high privacy protection score (0.95). It also maintains a low data loss rate of 0.01%, demonstrating enhanced robustness and real-time capability. These findings indicate that DQN-Raft+ effectively strengthens data security and privacy in IoT systems, offering a technically sound and efficient mechanism for secure data exchange. The study provides both a theoretical framework and practical direction for future research in secure IoT deployment.
Haoxiang Luo, Ruichen Zhang, Yinqiu Liu, Gang Sun · 6 authors
Low-altitude airspace is becoming a new frontier for smart city services and commerce. Networks of drones, electric Vertical Takeoff and Landing (eVTOL) vehicles, and other aircraft, termed Low-Altitude Economic Networks (LAENets), promise to transform urban logistics, aerial sensing, and communication. A key challenge is how to efficiently share and trust the computing utility, termed “computility”, of these aerial devices. We propose treating the computing power on aircraft as tokenized Real-World Assets (RWAs) that can be traded and orchestrated via blockchain. By representing distributed edge computing resources as blockchain tokens, disparate devices can form Low-Altitude Computility Networks (LACNets), collaborative computing clusters in the sky. We first compare blockchain technologies, non-fungible tokens (NFTs), and RWA frameworks to clarify how physical hardware and its computational output can be tokenized as assets. Then, we present an architecture using blockchain to integrate aircraft fleets into a secure, interoperable computing network. Furthermore, a case study models an urban logistics LACNet of delivery drones and air-taxis. Simulation results indicate improvements in task latency, trust assurance, and resource efficiency when leveraging RWA-based coordination. Finally, we discuss future research directions, including AI-driven orchestration, edge AI offloading and collaborative computing, and cross-jurisdictional policy for tokenized assets.
Abstract In the context of the IoT platform, the smart home represents a quintessential application scenario. Here, device-to-device (D2D) collaboration serves as the core element of its ecosystem, playing a crucial role in implementing diversified automated execution scenarios that are customized to fulfill user requirements. The progressive integration of edge computing and AI technologies has enhanced the collaboration among heterogeneous devices. Nevertheless, the conventional centralized D2D collaboration authorization decision-making supported by a single IoT Hub violates the Principle of Least Privilege (PoLP), which is a foundational design tenet that has been empirically validated as an optimal engineering practice for enhancing system security and reliability in IoT ecosystems. If there is a trade-off of PoLP violations, it fails to meet the users’ Quality of Experience (QoE). To address this issue, we propose D2DA, a distributed authorization decision-making model for smart home D2D collaboration, which constructs a distributed decision-making consensus network suitable for the edge side of smart homes by leveraging distributed ledger technology. D2DA presents a machine learning algorithm with a time complexity of O ( n ). Through this algorithm, consensus nodes can be efficiently and dynamically selected. Furthermore, D2DA ensures the security of the D2D collaboration process via wallets and hash verification. Extensive experiments conducted on a real-world smart home scenario validate that the decision-making latency of D2DA is on par with that of a single IoT Hub mode. The average latency for verifying the correctness of the newly added execution results is only 0.08% of the system time of D2DA, which is negligible.
The integration of blockchain technology with IoT architectures holds immense potential for advancing application design and enhancing security properties. However, the resource constraints typically present in IoT devices pose a challenge. This paper explores the feasibility of running a lightweight Bitcoin wallet on IoT devices and identifies the minimum requirements for their successful operation. A review of the literature is used to identify existing integration architectures and derive the wallet needs. The study evaluates performance metrics such as execution time, memory usage, network data transmission, and power consumption to determine the feasibility of deploying these architectures.
Ahmed M. Tawfik, Ayman Al-Ahwal, Adly S. Tag Eldien, Hala H. Zayed
Abstract In recent years, blockchain technology has emerged as a promising solution for securing electronic health records (EHRs) while preserving patient privacy. Traditional e-health systems facilitate EHR sharing among healthcare providers but also introduce significant privacy risks, such as unauthorized access and data breaches. Blockchain, when integrated with privacy-preserving techniques, enhances transparency, integrity, and availability in EHR management. Smart contracts further strengthen security by enabling automated authentication and access control. This paper provides a comprehensive survey of blockchain-based access control frameworks in healthcare, categorizing them into permissioned and permissionless approaches. It also explores cryptographic privacy-preserving techniques designed to mitigate privacy risks. Additionally, blockchain platforms and consensus protocols commonly used in these frameworks are analyzed. The methodology follows a structured paper selection process, leading to the final inclusion of 45 research papers focusing on blockchain-based privacy preservation and access control in healthcare. Furthermore, it presents real-world case studies that illustrate the practical implementation of blockchain-based access control in healthcare settings, highlighting their strengths and challenges. Finally, it identifies privacy-related challenges, open research issues, and future directions to guide further research in this evolving domain.
Remote service delivery and automation using Blockchain and Internet of Things (IoT) are revolutionising healthcare operations. Enhancing healthcare data interchange and providing real-time treatment is becoming more difficult due to the exponential growth of patient populations around the globe. It is still very difficult to develop a digital healthcare platform that is entirely decentralised, secure, trustworthy, interoperable, and scalable, even if existing studies have improved these platforms to improve patient outcomes and reduce hospital visits. This paper proposes a robust and scalable healthcare architecture using Blockchain smart contracts and IoT, with the integration of the InterPlanetary File System (IPFS). By securely storing sensitive medical records, the framework enhances data privacy and interoperability for patients as well as healthcare professionals. A device proxy monitors potentially vulnerable IoT devices and uses cryptography to ensure that data remains private. Experimental evaluations of the system’s performance have focused on key factors, including healthcare record upload, download, access, and mining times. The results show that public healthcare systems based on the Blockchain considerably boost efficiency and performance by integrating IPFS.
This article explores how the integration of Artificial Intelligence (AI), Machine Learning (ML), Web3.0, Blockchain, Metaverse, and Non-Fungible Tokens (NFTs) will revolutionize various aspects of public life globally over the next decade. We introduce novel perspectives such as AI-driven decentralized governance, blockchain-based universal basic income, and metaverse-enabled global education platforms. These technologies will transform global supply chains through AI-driven forecasting and blockchain-verified logistics, ensuring transparency and efficiency. Healthcare will advance with AI-powered telemedicine and personalized treatments, reducing disparities in underserved regions. Autonomous systems will enhance urban mobility and disaster response, fostering sustainable smart cities. Web3.0 will empower users with decentralized digital identities and data sovereignty, redefining advertising and social media through token-based models. Blockchain will secure academic credentials, streamline insurance, and enable transparent philanthropy, while carbon credit markets promote sustainability. The metaverse will revolutionize remote work, healthcare consultations, and cultural preservation through immersive virtual environments. NFTs will democratize real estate and creative economies, enabling tokenized ownership and secure voting systems. Synergistically, these technologies will create decentralized e-commerce, disaster response systems, and virtual innovation hubs, fostering equitable digital ecosystems. However, challenges like digital divides, AI biases, and blockchain scalability must be addressed to ensure inclusive adoption. This article envisions a future where these advancements redefine governance, economies, and social interactions, paving the way for an innovative, equitable global society. AI-driven avatars and decentralized AI training platforms will further enhance virtual collaboration, while tokenized cultural assets empower communities, ensuring a resilient, inclusive digital future.
Driven by globalization and digitization, the Mobile Industrial Supply Chain Internet of Things (IoT) has gradually developed, utilizing mobile devices and IoT technologies to enable real-time monitoring and efficient responses across various stages. However, with the growing demand for high-frequency data exchange, the Mobile Industrial Supply Chain IoT faces significant challenges in data security, authentication, and privacy protection. This paper proposes a security authentication scheme based on blockchain and group key management, leveraging the decentralized and tamper-resistant features of blockchain, the privacy-preserving authentication method of Zero-Knowledge Proofs (ZKP), and a hierarchical key management mechanism based on binary key trees. This approach aims to enhance the security and scalability of Mobile Industrial Supply Chain IoT. The experimental section simulates scenarios such as dynamic node addition and key updates, evaluating the performance in terms of encryption, decryption, and key management efficiency, thus demonstrating its superiority in multi-party collaborative environments.
R. Yuvarani, R Mahaveerakannan, T. Tamilvizhi, L Kartheesan
The integration of blockchain into 6G-enabled Internet of Medical Things (IoMT) networks promises secure and decentralized communication but introduces challenges related to energy efficiency, latency, and authentication overhead. Existing clustering and security schemes fail to balance these aspects effectively in heterogeneous networks. This paper proposes a novel energy-aware cluster head (CH) selection framework using Artificial Democratic Cuckoo Glowworm Remora Optimization (ADCGRO), integrated with a lightweight blockchain layer for secure authentication and data integrity. The system optimizes task allocation across advanced, intermediate, and normal IoMT devices to minimize energy depletion while meeting ultra-reliable low-latency communication (URLLC) requirements. Simulation results demonstrate that the proposed approach enhances network lifetime by 27%, reduces average latency by 35%, and achieves 99% authentication accuracy, surpassing baseline protocols such as LEACH and HEED. These results highlight the effectiveness of combining ADCGRO-based optimization with blockchain to enhance performance and security in 6G wireless networks.
Naser Abbas Hussein, Jihene Khoualdi, Ilhem Abdelhedi Abdelmoula, Hella Kaffel Ben Ayed
Internet of Things (IoT) has gripped domains with this ubiquitous connectivity, in-themoment data collection, and autonomous decision-making. But rising numbers of heterogeneous, extremely constrained IoT devices pose serious concerns regarding data privacy, security, and trust management, drawing great attention into these areas in the academic field and on all sides. Thus, blockchain technology came into the limelight for strengthening security and privacy in IoT systems in a decentralized manner, giving the system immutability, transparency, and distributed trust. This study proposes a Systematic Literature Review (SLR) of blockchain-based approaches that aim to enhance the IoT applications' privacy and security, focusing chiefly on healthcare, supply chains, and smart cities. The review uses a structured methodology to find, select, evaluate, and synthesize relevant peer-reviewed studies published between 2018 and 2025 taken from major scientific databases such as IEEE Xplore, ACM Digital Library, ScienceDirect, SpringerLink, and Scopus. Articles were also examined to narrow the scope of study and set the subject. The selected studies are analyzed and classified based on their security goals (e.g., confidentiality, integrity, authentication), privacy-preserving techniques (e.g., anonymization, differential privacy, zero-knowledge proofs), blockchain configurations (e.g., public, private, consortium), and consensus mechanisms. The findings reveal a growing body of research applying blockchain to a wide range of IoT domains, addressing diverse application domains such as healthcare, smart homes, industrial IoT, and agriculture, and demonstrating its potential to enhance data integrity, access control, and authentication. However, the integration of blockchain in IoT also faces challenges such as scalability, latency, and resource overhead, especially in real-time and constrained environments. This review offers a comprehensive synthesis of the state-of-the-art, identifies current limitations and research gaps, and proposes future research directions for building secure, efficient, privacy-aware, and scalable blockchain-enabled IoT systems.
The Internet of Things (IoT) has attained significant interest recently, particularly in the medical field due to the quick development of IoT devices. Medical related data contains a significant volume of personal information, and it is crucial to maintain privacy. As medical information becomes increasingly electronic in the era of big data, securely and accurately storing medical information is critical. However, the heterogeneity of information systems poses a significant challenge to their sharing. Moreover, medical data typically comprises sensitive information, and sharing it can potentially lead to breaches of personal privacy. Data sharing is a significant concern in healthcare because of privacy leakage and security issues. To combat this issue, this paper introduces the prediction and Provable Partitioned Secure Block Chain Principle (PPSBCP) technique is used to secure healthcare data sharing. Initially, in the healthcare data analysis phase, the Preprocessing and normalization are carried out by Z-score normalized for analysing the healthcare-sensitive margins. The SSIR (Sensitive Spectral Impact Rate) method is applied to find the sensitive records. Based on the impact margins, the Binomial Quadratic Sensitive Data Prediction (BQSDP) method is applied to categorize the sensitive and non-sensitive information. In the blockchain phase, create a Hash Index Policy (HIP) to encrypt the data using a Foldable Blockchain Encryption Standard (FBES). The Master Node Handover Authentication Policy (MNHAP) is applied to verify the private key in the data safety. The Distributed Hyper Ledger Mechanism (DHLM) is applied to make the chain transaction principle. The proposed system accomplishes high performance in security by achieving the parameters in verification and validation as well as compared to the existing systems.
The exponential growth of IoT data demands efficient, secure, and scalable storage solutions on one hand, and efficient data migration and retrieval on the other hand are essential for the systems to be practical and acceptable for different applications. The traditional cloud-based models face latency, security, and high operational costs, while existing bi-directional data storage and retrieval-based IPFS models are not computationally efficient and incur high gas costs at the cost of a necessary blockchain deployment. To overcome the challenges of efficient data migration, we initially developed a 2-way data storage and retrieval system as well as a scalable framework that dynamically monitors and transfers device-generated data to IPFS, records the content identifier(CID) on a blockchain, and enables secure, real-time access via smart contracts. Experimental results demonstrate that the existing work achieved an average data upload time of 117.12 sec for a file size of 500 MB; our framework achieves a faster upload time of 7.63 sec, marking a 93.47% improvement. We further optimize the proposed framework to reduce the file upload time incurred from the smart contracts by introducing a blockchain-inspired, lightweight, and customizable Python framework that replicates the storage and retrieval functionalities of a traditional blockchain, where the file upload time is 4.2 sec, further optimized by 45% from our previous approach, thus demonstrating its efficiency, security and suitability for deploy ment in real-time and critical IoT applications and outperforming the existing IPFS-smart contract based solutions.
In recent years, cloud marketplaces have emerged as dominant platforms for cloud service procurement. These marketplaces, led by major providers such as Azure, Amazon Web Services, and Google Cloud, feature services exclusively available on their own platforms, introducing limitations for end users. This paper explores the convergence of cloud computing, blockchain, and semantics, envisioning a marketplace where cloud providers can offer their cloud services and cloud consumers can efficiently discover, procure, and potentially resell these services. Semantic representations streamline service discovery and composition, enhancing interoperability. Blockchain technology and non-fungible tokens play pivotal roles in establishing a fully decentralized marketplace characterized by data verification and immutability. This enables autonomous contract validation and execution between cloud consumers and cloud providers, reducing reliance on intermediaries. This innovative fusion promises to reshape the landscape of cloud service procurement, making it more transparent and independent.
The rapid digitization of the healthcare sector has led to the generation of massive volumes of Electronic Health Records (EHRs), necessitating a robust, secure, and scalable system capable of efficiently managing and accessing this ever-growing data. Ensuring privacy, security, and scalability in managing voluminous and sensitive healthcare data, particularly when stored across various geographical locations, poses critical challenges that require innovative solutions. To address these issues, MeDiStore, a decentralized framework built on the Ethereum blockchain, is proposed. By integrating the InterPlanetary File System (IPFS), MeDiStore ensures scalable and secure storage while mitigating centralization risks and providing improved accessibility for EHRs. The framework leverages Elliptic Curve Cryptography (ECC) to encrypt and secure patient records, ensuring data ownership remains with the patient. To further enhance scalability, security, and reliability, of the blockchain network, the MeDiStore Trust Protocol, introduced a modified Proof of Stake (PoS) consensus mechanism that evaluates validators based on their network stake and reputation score, derived from their historical performance. Additionally, a Data Translation Layer is incorporated to ensure interoperability by converting EHRs into Fast Healthcare Interoperability Resources (FHIR) or Health Level 7 (HL7) systems without compromising security. Performance evaluation across 200 consensus rounds highlights metrics such as smart contract execution time, average IPFS file upload time, and reputation score behavior of validators. A comprehensive security analysis simulates Sybil attack scenarios, demonstrating the system's resilience through reputation-based validator selection. By integrating these factors, MeDiStore offers a scalable, secure, privacy-preserving, and interoperable solution tailored for efficient EHR management in the healthcare domain.
The interest in blockchain for Industry 4.0 applications and the integration of the Industrial Internet of Things (IIoT) has grown considerably. This is due to the unique characteristics of blockchain, including the immutability of the distributed ledger, transparency, traceability of transactions, and security based on cryptographic techniques that certify the integrity of the data. So, the integration of blockchain can enhance data integrity, transparency, and security while eliminating trusted third parties. However, these characteristics make blockchains difficult to scale and typically involve high costs for a large number of transactions. It makes it difficult to manage large amounts of data which are generally produced in IIoT environments. Some recent results have demonstrated how the use of private blockchains can improve the issues of scalability and transaction costs. This paper addresses the following research question: Can blockchain technology, in its current state, be suitable for implementing industrial monitoring applications that use IIoT devices? Our objective is to propose a blockchain-based application integrated with IIoT devices in order to control the air and water pollution produced by industrial activities. The application we propose complies with current European regulations. Finally, we perform an empirical evaluation of the solution's performance to understand its applicability in real-world scenarios.
The increasing reliance on cloud services demands advanced security mechanisms to protect sensitive data and ensure robust access control. This study addresses critical challenges in cloud security by proposing a novel framework that integrates blockchain-based smart contracts to enhance authorization and authentication processes. Smart contracts, as self-executing agreements embedded with predefined rules, enable decentralized, transparent, and tamper-proof mechanisms for managing access control in cloud environments. The proposed system mitigates prevalent threats such as unauthorized access, data breaches, and identity theft through an immutable and auditable security framework. A prototype system, developed using Ethereum blockchain and Solidity programming, demonstrates the feasibility and effectiveness of the approach. Rigorous evaluations reveal significant improvements in key metrics: security, with a 0% success rate for unauthorized access attempts; scalability, maintaining low response times for up to 100 concurrent users; and usability, with an average user satisfaction rating of 4.4 out of 5. These findings establish the efficacy of smart contract-based solutions in addressing critical vulnerabilities in cloud services while maintaining operational efficiency. The study underscores the transformative potential of blockchain and smart contracts in revolutionizing cloud security practices. Future research will focus on optimizing the system’s scalability for higher user loads and integrating advanced features such as adaptive authentication and anomaly detection for enhanced resilience across diverse cloud platforms.
Evangelos Stavropoulos, Ioanna Karampela, Arjun Singh, Maria K. N. Fountoulakis · 8 authors
—The European research project GHOST challenges the traditional cyber security solutions for the Internet of Things (IoT) sector by exploiting novel technologies, such as blockchain, to provide resilience and integrity of decision making on the communication exchange in a smart home context. When it comes to novel cyber security solutions for extremely heterogeneous environments like IoT and smart homes, the key focus is typically given to the understanding of network activities and elimination of suspicious traffic. The GHOST project adds an extra dimension to this approach by integrating blockchain technology at its core decision mechanism. On a daily basis, each GHOST installation is encountering malicious behaviour and suspicious IoT communications, where easy information sharing with other installations, as well as decentralised decision making, are mandatory features for the efficient protection of the end-user. GHOST's Smart Contracts (SC) are designed to tackle in an easy, yet productive way, the reporting on suspicious IP addresses which the IoT devices in a smart home are trying to communicate with. Two variations of blacklisting smart contracts are presented in this paper, covering a diverse spectrum of possible attack vectors while closely following the Privacy by Design (PbD) principles. A reputation scoring scheme for malicious IPs reporting is integrated in the SC, uncovering the implementation details on the penalisation of existing entries in case of malicious behaviour of reporting devices
Sadly Syamsuddin, Salama Manjang, Muhammad Bachtiar Nappu, Ady Wahyudi Paundu
This study proposes the integration of a hybrid Proof of Work/Proof of Stake (PoW/PoS) consensus mechanism with a Long Short-Term Memory (LSTM) model for anomaly detection in blockchain-based microgrids. The hybrid PoW/PoS model is designed to address common issues in blockchain systems, such as 51% attacks, double-spending, and high energy consumption, by optimizing energy usage and enhancing security. Simulation results show that the system can process transactions with an average throughput of 37.25 transactions per second (TPS), an average latency of 26.84 milliseconds per transaction (ms/tx), and extremely efficient energy consumption per transaction (0.01 kWh/tx). The LSTM model applied for anomaly detection achieves an 89.10% detection rate, a 0.00% false positive rate, and a 0.12 s recovery time, indicating the system's reliability in facing attacks. The hybrid PoW/PoS system demonstrates advantages in both energy efficiency and resilience to attacks compared to individual PoW and PoS systems. This research contributes to the development of safer, more efficient, and scalable blockchain-based microgrids by integrating Artificial Intelligence (AI) to strengthen the system against anomalies and threats.
Blockchain technology has become an essential tool for enhancing reliability and security across several industries, including the healthcare sector. In this work, we propose and implement an Ethereum-based blockchain framework to decentralize electronic health records (EHRs) at Tumakuru Siddaganga Hospital. The system establishes an append-only chain of transaction blocks that guarantees the confidentiality, auditability, and integrity of patient health records. By design, only authorized healthcare professionals can access patient data, and even then, only with the patient’s explicit consent—ensuring a privacy-preserving access model. Our approach demonstrated a 40% reduction in data access delays and eliminated unauthorized access attempts through smart contract-based access control. The decentralized nature of the framework reduces reliance on centralized databases, significantly lowering the risk of data tampering and breaches. Additionally, the implemented consensus protocol ensures that only verified transactions are recorded, maintaining consistency across distributed nodes. Compared to traditional systems, our blockchain-based solution improved the traceability of health data access events by 100%, ensuring transparency and accountability. These findings validate that blockchain technology can substantially enhance data sharing, integrity, and patient control in modern healthcare systems.
The pharmaceutical supply chain has a critical component, the Drug Traceability System, which tracks drugs from manufacturers for further processing and distribution. The integration of blockchain technology yields a secure solution for monitoring drugs throughout the supply chain management process. The paper proposes a novel Blockchain-enabled Secured Vertical Aggregation Algorithm (BSVA) by leveraging the Hyperledger model. The proposed model minimizes the requirement for a centralized authority to ensure privacy while also enhancing scalability to reduce response time in the process of managing transactions on the Blockchain. The Certificate Authority is used to maintain a secure data-sharing process. The robust aggregation is used for the local models to process the chain code, ensuring the successful execution of the secured transaction. The smart contract is deployed into a blockchain model as the block is stored and linked to the distributed Ledger. The decentralized framework is used by chain code, which guarantees that transactions are highly transparency. The performance parameters demonstrate the efficiency of the proposed model by enhancing the overall performance of the drug traceability system, as the proposed algorithm ensures the integrity of pharmaceutical products throughout the supply chain.