The rapid expansion of the Internet of Things (IoT) is driving the integration of billions of connected devices across various domains, including healthcare, transportation, and smart urban systems. Although this proliferation offers considerable advantages in terms of functionality and operational efficiency, it also brings to the forefront a range of pressing concerns, particularly in relation to security, reliability, and privacy. These challenges are largely rooted in the decentralized and dynamic architecture of IoT ecosystems. In this context, trust and reputation mechanisms have become increasingly vital for enabling secure and reliable interactions between devices and users. This paper examines recent advances in trust management models tailored to IoT environments, with a focus on approaches leveraging blockchain technologies, machine learning techniques, and edge or fog computing paradigms. We assess the practical implications of these solutions, discussing both their strengths and inherent limitations. Furthermore, we identify key open issues such as scalability, data protection, and interoperability across platforms, and we outline potential research directions to support the development of more robust and adaptable trust frameworks for the evolving IoT landscape.
Traditional blockchain protocols incentivize constant participation through resource-intensive mechanisms such as Proof-of-Work (PoW) or Proof-of-Stake (PoS). However, this model leads to excessive energy consumption and network redundancy. This paper proposes a novel consensus auxiliary protocol called Proof-of-Inactivity (PoI), wherein nodes earn trust by deliberately abstaining from consensus activities for defined, randomized periods. Inactivity is cryptographically proven via time-locked commitments and publicly verifiable absence proofs. This paradigm aims to reduce redundant communication, lower energy usage, and support lightweight node participation without compromising network integrity. The protocol is introduced alongside a security assessment, performance analysis, and possible energy savings based on simulated scenarios, including conversations about DIDs, zero-knowledge mechanism, hybrid consensus, and adaptability.
The rise of Intelligent Consumer Electronics (ICE), including smart home hubs and wearable devices, requires decentralized mechanisms for secure firmware validation, access control, and tamper-resistant logging. Centralized systems remain vulnerable to spoofed updates, opaque logging practices, and limited scalability. To address these challenges, we present a blockchain-based framework that integrates hash-based firmware verification, smart contract-backed access logging, elliptic curve signatures, and TLS-secured transport. Our evaluation, conducted on constrained device profiles (1 vCPU, 512MB RAM, 10 Mbps bandwidth), employed four platforms: Hyperledger Fabric (Raft), IOTA (Tangle), Algorand, and Ethereum (PoA). IOTA demonstrated the lowest latency (220 ms) and minimal resource consumption (42MB RAM, 34% CPU), while Algorand achieved peak throughput (910 tx/s) with 95% consistency. Ethereum-PoA minimized storage requirements (2.8MB per 1,000 logs), whereas Fabric exhibited higher latency (570 ms) and resource load (74MB RAM, 51% CPU) but provided strong audit guarantees. Spoofed firmware was rejected in 100% of cases, and unauthorized logs were blocked in over 97.5% of attempts. Privacy was ensured using pseudonymous identifiers and selective logging. Adversarial dynamics such as packet loss, jamming, and consensus forking were modeled. Despite partial offloading to a gateway node, auditability and verification upheld decentralized trust. These results confirm the feasibility of blockchain-secured ICE and its resilience to both operational and adversarial threats.
In this paper, we design, implement, and empirically evaluate a tamper-evident, blockchain-secured solar energy logging system for resource-constrained edge Internet of Things (IoT) devices. Using a Merkle tree batching approach in conjunction with threshold-triggered blockchain anchoring, the system combines high-frequency local logging with energy-efficient, cryptographically verifiable submissions to the Ethereum Sepolia testnet, a public Proof-of-Stake (PoS) blockchain. The logger captured and hashed cryptographic chains on a minute-by-minute basis during a continuous 135 h deployment on a Raspberry Pi equipped with an INA219 sensor. Thanks to effective retrial and daily rollover mechanisms, it committed 130 verified Merkle batches to the blockchain without any data loss or unverifiable records, even during internet outages. The system offers robust end-to-end auditability and tamper resistance with low operational and carbon overhead, which was tested with comparative benchmarking against other blockchain logging models and conventional local and cloud-based loggers. The findings illustrate the technical and sustainability feasibility of digital audit trails based on blockchain technology for distributed solar energy systems. These audit trails facilitate scalable environmental, social, and governance (ESG) reporting, automated renewable energy certification, and transparent carbon accounting.
The incorporation of the Internet of Things (IoT) into daily life has brought about challenges related to security and privacy. Smart home security systems using physical locks connected to the internet continue to be susceptible to unrecognized key duplication and unauthorized entry. To overcome this challenge, this work proposes a decentralized smart lock system using the blockchain technology as a means of providing improved access control and security in smart homes. The proposed system integrates the coupling of an IoT device with a keypad entry and a Solidity-based smart contract logic on the IOTA Ethereum Virtual Machine (EVM) test network. A webbased frontend using Node.js enables homeowners to grant access permissions remotely, where Web3.py ensures safe blockchain interactions. The initiative eliminates the vulnerability that comes with physical keys, facilitates secure remote access control, and improves the safety using hashed access codes, time-limited procedures, and non-repudiation of transactions. Experimental results further show that the proposed IOTA-based smart lock system keeps the usage of resources lower compared to existing Ethereum-based solutions.
The energy sector faces inefficiencies, fraud, and lack of transparency, while the traditional peer-to-peer (P2P) energy trading market faces challenges of trust, interoperability, and flexibility. This paper proposes an innovative solution leveraging blockchain technology to address these issues. By representing energy units as unique, verifiable Non-Fungible Tokens (NFTs), our aim is to create a transparent, secure, and efficient energy marketplace. Our architecture integrates a Web3 marketplace with smart contracts to manage trading transactions, NFTs to visualize energy, and a sophisticated loyalty program to incentivize user participation. Furthermore, the platform improves user accessibility through cross-chain token bridging via the Across Protocol, enabling seamless fund transfers from Layer 1 or other Layer 2 networks to the Base network. These features collectively reduce entry barriers and expand market participation. Using blockchain technology, our solution addresses the limitations of traditional systems, offering enhanced security, user engagement, improved efficiency, and simplified access to the energy marketplace.
In an uncertain world filled with cyberthreats, blockchain has proven to be a revolutionary technology of significant value to most industries. While blockchain is used extensively in the fields of energy, finance and governance, healthcare is among the key sectors whose applications have been most evident as far as its adoption into these sectors is concerned. Since data is currently regarded as both an asset and currency, security has emerged as a key issue especially in healthcare as more and more data breaches have emphasized the need for enhanced planning, requirements analysis and implementation of strong cybersecurity models. This paper introduces a cloud-based blockchain architecture The approach organizes network participants into clusters, with each cluster maintaining a single copy of the blockchain. This design introduces a new blockchain architecture tailored for secure healthcare data management, significantly lowering both computational demands and communication overhead particularly when compared with conventional Bitcoin networks and existing lightweight blockchain models, while at the same time, investigating how the proposed design adequately mitigates known security threats. Experimental results show that, with increasing number of nodes, the proposed model accelerates the updates of ledger, It achieves a 63% reduction in computational load while also decreasing network traffic by 10%.
In recent years, Femtech has emerged as a growing market category dedicated to women’s health technologies. Despite its rapid expansion, this relatively new and largely unregulated sector has experienced several concerning security breaches that compromise user privacy and intimacy. To address this critical gap between innovation and protection, we propose a novel blockchain-based consent management framework specifically designed for Femtech applications. Our solution leverages distributed ledger technology and smart contracts to create a transparent, immutable system where users can granularly control access to their sensitive health data.
T. Ratha Jeyalakshmi, Alamma Bh, H S Harshitha, K. Agarwal R.
Privacy of users and security of data are important issues that will be exposed to use in the Metaverse by use of Digital Twins (DTs). The current paper suggests a privacy-preserving system, which combines Zero-Knowledge Proofs (ZKPs) of secure identity verification and Federated Learning (FL) of decentralized model training. The framework allows for alleviating the risk of storing data in central facilities and preventing unauthorized access by locally processing data and using cryptographic solutions. The results produced by the evaluation prove that the proposed system is capable of attaining the necessary level of privacy of its users and ensuring reliable and scalable communications within the Metaverse applications.
Mohamad Sheikho Al Jasem, Trevor De Clark, Ajay Kumar Shrestha
The convergence of decentralized artificial intelligence (DAI), blockchain technology, and smart contracts is reshaping the design and governance of intelligent systems. As these technologies rapidly evolve, addressing privacy within their architecture, usage models, and associated risks has become increasingly critical. This systematic literature review examines architectural patterns, governance frameworks, real-world applications, and persistent challenges in DAI systems. It identifies prevailing designs such as federated learning integrated with consensus protocols, smart contract-based incentive mechanisms, and decentralized verification methods. Drawing from a diverse body of recent literature, the review highlights implementations across sectors, including healthcare, finance, IoT, autonomous systems, and intelligent infrastructure, each demonstrating significant contributions to privacy, security, and collaborative innovation. Despite these advancements, DAI systems face ongoing obstacles such as scalability limitations, privacy trade-offs, and difficulties with regulatory compliance. The review emphasizes the need for integrative governance approaches that balance transparency, accountability, incentive alignment, and ethical oversight. These elements are proposed as co-evolving pillars essential to establishing trustworthiness in decentralized AI ecosystems. This work offers a comprehensive review for understanding the current landscape and guiding the development of responsible and effective DAI systems in the Web3 era.
In today's rapidly evolving landscape of smart city applications, particularly in sensitive areas like the healthcare sector, safeguarding the security, integrity, and privacy of data has become a significant and challenging concern. Specifically in the healthcare sector, the sharing and access of patient records across various stages of care by doctors, nurses, pharmacies, and diagnostic centers introduce new complexities and potential vulnerabilities. However, these challenges intensify more in the case of distributed healthcare networks where data is fragmented across institutions. This work addresses issues such as data vulnerability and misuse in distributed healthcare environments by proposing a Blockchain-enabled Distributed Healthcare System (BeDHS). The model is designed to facilitate secure, transparent, and privacy-preserving collaboration among healthcare entities. It adopts a hybrid approach, integrating a quantum key-based image encryption technique to enhance the security of health records. The encrypted images are securely stored in the InterPlanetary File System (IPFS) to ensure data integrity and availability. Additionally, a Federated Learning (FL) framework is employed to enable collaborative training of AI models across institutions without exposing sensitive patient data. The proposed BeDHS model is implemented using Solidity-based smart contracts on the Ethereum blockchain, ensuring decentralized and tamper-resistant operations. Simulation results demonstrate that the proposed model outperforms existing healthcare data management systems in terms of efficiency and security. • A blockchain-enabled distributed healthcare system is proposed, where the number of healthcare institutions of a smart city are integrated to form a collaborative and transparent model for sharing health records while maintaining security, privacy, and immutability. • A Quantum-Chaos-Encryption cryptographic technique integrated with blockchain for protecting digital documents and medical images from unauthorized access. • To build a privacy-preserved distributed-collaborative healthcare system, a federated learning approach is incorporated that trains the AI models directly at the data source of multiple healthcare institutions while eliminating the need to transfer between the institutions.
The merging of Artificial Intelligence (AI) with the Internet of Things (IoT) has sparked a swift transformation in AIoT systems, allowing for real-time intelligence in smart cities, industries, and homes. Yet, these advancements bring about increasing worries regarding data privacy, device trust, and potential security threats-particularly with the emergence of quantum computing. This paper introduces a secure and privacy focused AIoT framework that integrates Federated Learning with Differential Privacy, Zero-Knowledge Proofs (ZKP) for device authentication, and Post-Quantum Cryptography(CRYSTALSKyber) to protect model updates on the blockchain. Unlike conventional methods that depend on cloud processing and expose sensitive data, this innovative system allows for on-device model training through TinyML, ensuring that data remains on the device. A practical implementation using ESP32-S3 devices in both a smart classroom and home environment showcases the framework's effectiveness. The results indicate a 12% boost in privacy, a 35% reduction in communication costs, and an 8.7% increase in model accuracy compared to traditional methods. This architecture tackles significant unresolved challenges in AIoT by securing data at the edge, preventing device spoofing, and preparing for future quantum threats-making it an excellent choice for privacy-sensitive, real-time AIoT applications.
Blockchain has evolved from cryptocurrency infrastructure to a foundation for decentralized finance, supply chain, and digital identity. However, widespread adoption faces three main barriers that are high energy use from traditional consensus, fragmented networks, and static, rule-based smart contracts. This work presents EcoChainX, a modular framework integrating AI-driven automation, sustainable consensus, robust interoperability, and advanced privacy features. Its four-layer architecture consists of AI modules for anomaly detection and smart contract optimization, energy-efficient consensus protocols, cross-chain interoperability, and privacy-preserving technologies such as zero-knowledge proofs and quantum-resistant cryptography. Through theoretical modeling, prototyping, and empirical testing, EcoChainX addresses scalability, sustainability, security, and privacy. By addressing them, this framework paves the way for responsible blockchain ecosystems capable of supporting the next generation of decentralized applications. Empirical results demonstrate that EcoChainX achieves a 97% reduction in energy consumption compared to traditional Proof-of-Work systems, increases transaction throughput by over 20 times (exceeding 10,000 TPS), reduces smart contract vulnerabilities by 60 % through AI-driven anomaly detection, and enables cross-chain transactions with a latency reduction of 80 %, establishing a new benchmark for sustainable and interoperable blockchain infrastructures.
Jonas Lopes de Vilas Boas, Ygor S. Costa, Rodrigo da Rosa Righi, Antônio Marcos Alberti · 5 authors
Reliable vaccine tracking and monitoring during transport and storage are essential to ensure dose effectiveness while minimizing waste. However, current solutions face challenges related to reliability, immutability, security, transparency, flexibility, extensibility, patient support, trust, and cost. Centralized systems are vulnerable to fraud, tampering, and manipulation, often relying on manual service contracts and lack of attested IoT devices to ensure data authenticity. Moreover, most existing platforms do not provide tamper-proof, near real-time monitoring, resulting in operational vulnerabilities and increased costs. This article presents Coldnet, a novel architecture for vaccine tracking and tracing that addresses these issues by: (i) integrating IoT device attestation with the registration of immutable data and flexible monitoring attributes; (ii) using Blockchain-based smart contracts to automatically manage tracking and monitoring clauses, improving security and enabling dynamic rule management; (iii) offering intuitive interfaces to support patient access to delivery information; and (iv) deploying an affordable, user-friendly IoT prototype to monitor and report vaccine status. A case study demonstrates Coldnet's feasibility, with an average delay of 20 seconds for recording and checking conditions — suitable for real operations. A simulation evaluating scalability and the impact of IoT attestation shows transaction costs of US$1.51 for ten vaccine batches with five monitored properties each, a cost deemed acceptable for the added features. Execution delays remained stable (0.85–0.92 seconds), with negligible impact from attestation. Coldnet contributes to reliable vaccine logistics, improving public health efforts by strengthening trust, transparency, and data integrity in vaccination campaigns.
Blockchain is expected to play a key role in securing next generation communication systems, i.e., B5G and 6G, which will be highly decentralised, with high integration of edge computing, device-to-device (D2D) communications, and notably IoT networks. This paper addresses a fundamental bottleneck of blockchain; the simulation of consensus algorithms. State-of-the-art blockchain consensus algorithm simulators are built on general data that do not consider resource-constrained devices. These simulators have limitations in performance measurement (energy, latency, and throughput) and testing of security attacks, including DoS, Sybil, and 34% or 51% attacks). This paper introduces a blockchain Internet of Things consensus algorithm (BICA) simulator, which offers a framework for testing consensus algorithms with adaptable IoT data in various attack scenarios. It evaluates metrics such as latency, throughput, and attack resilience, providing insights into their capabilities under diverse network conditions. A case study involving Proof of Stake (PoS), Delegated Proof of Stake (DPoS), Proof of Elapse Time (PoET), Proof of Authority (PoA) and Practical Byzantine Fault Tolerance (PBFT) showed PBFT’s superior performance and security against vulnerabilities such as Sybil, DoS, and 34-51% attacks. BICA’s block-creation speed surpasses that of the existing simulators.
Organ donation and transplantation systems are complex, sensitive, and often hindered by inefficiencies, lack of transparency, and data integrity issues. Traditional centralized systems struggle to manage consent, allocation, and tracking of organs in a secure and auditable manner. This paper proposes a blockchain-based application using a private Ethereum network to streamline and decentralize the organ donation process across hospitals. The system employs smart contracts and algorithm-driven matching to ensure secure donor registration, real-time tracking of organs, transparent allocation based on medical criteria, and immutable audit trails. Six core algorithms are implemented to manage consent, priority allocation, organ transport, and compliance verification. The experimental results demonstrate that the proposed system enhances privacy, accountability, and operational efficiency compared to existing methods. This solution not only reduces the risk of organ misuse and illegal trade but also builds trust among stakeholders, laying a strong foundation for ethical and technologically advanced organ donation management.
Chetan Chauhan, Pradeep Laxkar, Ram Kumar Solanki, S. R. Parihar · 6 authors
Blockchain technology has emerged as a promising paradigm for addressing the inherent vulnerabilities of Internet of Things (IoT) networks. Conventional IoT systems rely on centralized architectures that are prone to single points of failure, data breaches, and unauthorized access. This paper presents a blockchain-enabled secure communication framework for smart IoT systems that integrates symmetric encryption, distributed ledger validation, and smart-contract–driven access control. The proposed model is formalized through mathematical definitions of encryption, hashing, and contract execution, and validated using simulation tools such as NS-3 and Ethereum-based test environments. Comparative results demonstrate that the framework significantly improves communication security, data integrity, and resistance to cyberattacks while reducing latency and energy consumption relative to traditional models. The findings suggest that blockchain integration provides a scalable, resilient, and efficient foundation for trustworthy IoT communication in smart environments.
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.
Chigozie Athanasius Nnadiekwe, Collins Izuchukwu Okafor, Ikechi Saviour Igboanusi, Jae Min Lee · 5 authors
SoldierCare is a real-time, blockchain-enabled Internet of Medical Things (IoMT) framework designed to enhance military personnel safety through integrated health monitoring and cyberattack detection. The system employs a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model trained on the WUSTL-EHMS-2020 dataset, combining physiological sensor data and network traffic to identify both health anomalies and malicious activities with high accuracy. A smart contract-enabled Ethereum blockchain ensures the integrity and traceability of alerts by immutably logging metadata, while detailed data is stored off-chain in IPFS to reduce on-chain overhead. The architecture supports edge deployment, enabling low-latency inference and autonomous operation in mission-critical environments. Experimental results demonstrate a detection accuracy of 98.6%, with efficient scaling and minimal false detections. Optimizations such as transaction batching enhance blockchain performance under increasing load. SoldierCare represents a secure, scalable solution that fuses AI, fog computing, and blockchain to provide resilient operational support in dynamic battlefield scenarios.
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.