Blockchain Papers

Mahalinoro Razafimanjato, Malik Muhammad Saad, Dongkyun Kim

The Internet of Vehicles (IoV), a critical component of Intelligent Transportation Systems (ITS), enhances driving safety and traffic efficiency through real-time data exchange. However, the dynamic and heterogeneous nature of IoV introduces significant security and trust challenges. To address these, trust management systems have emerged as vital mechanisms to ensure the reliability and integrity of data exchanged between vehicles. Blockchain technology offers a robust framework for addressing security and trust issues in IoV environments. The decentralized, tamper-resistant, and transparent nature of the blockchain makes it suitable for complex vehicular environments. This survey provides an overview of state-of-the-art blockchain-based trust management systems in IoV. Following a systematic literature review that filtered 8,280 publications to 63 core studies from 2019 to 2024, we present a thematic classification of existing solutions, focusing on those employing public and private blockchains. Unlike previous surveys, our work focuses specifically on the intersection of blockchain and trust management systems in IoV by analyzing approaches across four dimensions: trust computation methods, such as game theory and AI-driven models; blockchain scaling solutions, including sharding, sidechains, and optimized consensus mechanisms; integration with emerging technologies such as 5G/6G, Digital Twins, and Federated Learning; and security and privacy mechanisms. Finally, this survey identifies current challenges and provides future research directions, highlighting the need for more scalable, adaptive, secure, and privacy-preserving trust management systems in IoV.

Dong‐Seong Kim, Esmot Ara Tuli, Igboanusi Ikechi Saviour, Md Mehedi Hasan Somrat · 5 authors

Technological advancements have fostered ubiquitous connectivity, driving the adoption of cloud computing and cloud-based services and applications for maintenance and management purposes. Consequently, cloud computing and cloud-based services have gained popularity for their scalability and efficiency in maintenance and management. However, such interconnected systems are inherently vulnerable to cybersecurity threats, including unauthorized access, data breaches, and others. Blockchain technology, initially popularized through cryptocurrencies, has proven to be a robust and reliable solution for various applications beyond financial transactions, such as supply chain management and secure data sharing. The integration of blockchain with cloud computing has given rise to the concept of “Blockchain as a Service” (BaaS), which provides developers with scalable and ready-to-use blockchain frameworks without the need for backend management. The current blockchain network has limitations such as low transaction per second (TPS), prolonged mining times, and other challenges that make it difficult for certain service-oriented applications. To address these issues, this paper introduces a hybrid on-off chain, edge-enabled BaaS solution called Pure Chain for service computing. Pure Chain refines the consensus algorithm, enhances the mining process, and enables seamless edge-supported online-offline hybrid transactions. Moreover, modified blockchain layers to improve efficiency and scalability. Pure Chain facilitates blockchain-enabled services and smart contract deployment in a cloud computing environment. Pure Chain optimizes energy consumption and delivers transaction speeds that are 12 times faster than conventional blockchain networks.

SUN Kangkang, LI Jianhua, CHEN Xiuzhen, GUO Minyi

With the advancement of edge intelligence technology and the acceleration of urbanization, intelligent transportation systems (ITS) have experienced rapid development. Vehicle-road-cloud (VRC) collaboration was enabled through the coordinated sharing of vehicle-to-vehicle (V2V), vehicle-to-road (V2R), and vehicle-to-cloud (V2C) data in the Internet of vehicles, thereby constructing a more efficient cooperative intelligent transportation system (C-ITS). However, numerous security threats in VRC collaboration were found to severely impede the development of cooperative autonomous driving. The development status of VRC collaboration was first summarized, and the history of autonomous driving and the VRC-based autonomous driving environment were elaborated. Subsequently, attacks and security defense technologies in VRC collaboration were systematically categorized into two types: classical information security mechanisms and defense technologies, which were detailed from five aspects—information availability, integrity, confidentiality, authenticity, and non-repudiation; and machine learning-based security threats and defense technologies, which were analyzed from both centralized and distributed perspectives. Finally, future development directions and research priorities of VRC collaborative security technologies were forecasted, primarily covering federated learning, blockchain technology, secure multi-party computation, zero-knowledge proof, and differential privacy technology.

Rajasekaran P, M. Duraipandian, Johny Renoald Albert

The increasing rate of growth of the Internet of Things (IoT) in cloud-hospitality health has brought in data storage, transmission, and security challenges with the advent of quantum-enabled threats. Traditional compression methods struggle with computational inefficiency and the threat of invasion of privacy. This paper proposes a Quantum-Enhanced Zero-Knowledge Healthcare Compression Network for solving these challenges by combining Zero-Knowledge Proofs and Quantum-Inspired Deep Learning. The main goal is to provide privacy-preserving, efficient data compression along with optimizing computation costs and safeguarding sensitive healthcare records. Drawbacks in present cryptographic techniques, e.g., high computational costs in homomorphic encryption and scalability limitations in blockchain, require a novelty Adaptive Quantum-Assisted Zero-Knowledge Verification and Quantum Fusion-AutoCNN Encoder (QF-AutoCNN) to overcome this research. This work’s originality lies in combining Quantum zk-SNARKs, Hybrid Quantum Feature Encoding, and Reinforcement Learning-Based Challenge Optimization to provide better security, compression ratio, and verification efficiency. Experimental results show better accuracy (0.9816), improved F-measure (0.9709), and less computational overhead, better than other current methods such as convolutional neural networks-encryption and proxy re-encryption. This research greatly adds to safe cloud healthcare IoT by lessening privacy threats, maximizing storage space, and minimizing processing time, guaranteeing real-time handling of medical information.

Marta Kovačević, Luka Petrovic

Blockchain has moved from a cryptocurrency infrastructure to a coordination technology for modern communication systems. This review examines how blockchain is being embedded into next-generation communication environments, with particular attention to Internet of Things deployments, edge-cloud collaboration, cyber-physical infrastructures, security and privacy management, smart grids, vehicular networking, and emerging 5G/6G ecosystems. Following the logic of recent survey work on blockchain-enabled communications, the article synthesizes representative peer-reviewed studies, clarifies the blockchain mechanisms that matter for communication engineering, and organizes the literature around application layers rather than isolated protocols. The review shows that blockchain creates value when communication systems require shared trust, auditable automation, decentralized identity, incentive-compatible coordination, or tamper-resistant data exchange across organizational boundaries. At the same time, real deployment remains constrained by throughput, latency, storage overhead, interoperability, privacy leakage, governance complexity, and uneven energy efficiency across consensus designs. Building on both communication-network research and information-systems scholarship, the article develops an integrated analytical view of when blockchain genuinely improves communication architectures and when lighter coordination mechanisms are preferable. The paper concludes by identifying future directions around lightweight consensus, AI-native blockchain orchestration, cross-chain communication fabrics, privacy-preserving verification, and programmable trust for 6G and autonomous infrastructures.

Adam Zahir, Milan Groshev, Carlos J. Bernardos, Antonio de la Oliva

Edge computingbrings computation near end users, enabling the provisioning of novel use cases. To satisfy end-user requirements, the concept ofedge federationhas recently emerged as a key mechanism for dynamic resources and services sharing across edge systems managed by different administrative domains. However, existing federation solutions often rely on pre-established agreements and face significant limitations, including operational complexity, delays caused by manual operations, high overhead costs, and dependence on trusted third parties. In this context, Distributed Ledger Technologies (DLTs) such asblockchaincan create dynamic federation agreements that enable service providers to securely interact and share services without prior trust. This article first describes the problem of edge federation, using the standardized ETSImulti-access edge computing (MEC)framework as a reference architecture, and how it is being addressed. Then, it proposes a novel solution usingblockchainandsmart contractsto enable distributed MEC systems to dynamically negotiate and execute federation in a secure, automated, and scalable manner. We validate our framework’s feasibility through a performance evaluation using a private Ethereum blockchain, built on the open-source Hyperledger Besu platform. The testbed includes a large number of MEC systems and compares two blockchain consensus algorithms. Experimental results demonstrate that our solution automates the entire federation lifecycle-from negotiation to deployment–with a quantifiable overhead, achieving federation in approximately 18 seconds in a baseline scenario. The framework scales efficiently in concurrent request scenarios, where multiple MEC systems initiate federation requests simultaneously. This approach provides a promising direction for addressing the complexities of dynamic, multi-domain federations across the edge-to-cloud continuum.

Jing Zhan, Xin Liu, Zhiqiang Zeng, Le Xiang

No abstract is available for this record.

Sompurna Bhadra, Gunjan Mukherjee, Jayanta Aich, Subrata Sinha

The COVID-19 pandemic has accelerated the adoption of digital health solutions such as telemedicine, Internet of Medical Things (IoMT), and AI-based diagnostics, enabling remote monitoring and contactless consultations. While IoMT devices—including wearable sensors and implantables—have enhanced continuous healthcare delivery, they have also introduced challenges related to security, privacy, interoperability, and latency. Traditional blockchain frameworks, though effective in ensuring decentralized trust and immutability, are resource-intensive and unsuitable for constrained IoMT environments. To address these limitations, this study proposes a Lightweight Blockchain–IoMT framework tailored for secure remote healthcare in the post-pandemic era. The proposed architecture follows a three-tier design: (i) the IoMT Device Layer for real-time physiological data collection, (ii) the Fog/Edge Layer functioning as blockchain gateways for authentication and pre-processing, and (iii) the Cloud Layer for storage, analytics, and decision support. By incorporating lightweight consensus mechanisms such as Proof-of-Authentication (PoAh) or Delegated Proof-of-Stake (DPoS), the system minimizes latency and energy consumption compared to Proof-of-Work. Security is reinforced through elliptic curve cryptography (ECC) and smart contracts, ensuring data confidentiality, integrity, and controlled access, while complying with global standards such as HIPAA and GDPR. Experimental analysis demonstrates that the lightweight blockchain–IoMT framework outperforms conventional blockchain models in transaction throughput, scalability, and energy efficiency. Moreover, the integration of machine learning within the cloud layer supports predictive analytics and personalized care.

Rui Han, Bin Yuan, Weizhong Qiang, Deqing Zou · 5 authors

The widespread use of IoT devices in the accommodation and hospitality sectors has created demand for temporary device-permission sharing and transfer. Prior work has largely focused on security issues in device permission sharing, with far less attention devoted to device permission transfer. However, inappropriate access control management during device permission transfer can also lead to violations of the users' expectations of control over their devices. For example, a malicious host retaining or regaining access to a camera after its permission has been transferred to a tenant. In this paper, we present the first systematic study on understanding and enhancing the security of device permission transfer in IoT leasing. To this end, we propose Forseti, a new authorization framework that leverages zero-knowledge proof and a decentralized ledger to ensure that the rights of both hosts and tenants are not violated. Our evaluation demonstrates that Forseti is effective, efficient, scalable, and compatible with existing IoT platforms.

Akash Shinde, K. S. Radha, Eesh Pratap Singh, Amresh Kushwaha

Event ticketing systems have long faced challenges such as counterfeiting, scalping, and lack of transparency in resale markets. To address these issues, this research presents the design and development of a blockchain-based ticketing platform that leverages Non-Fungible Tokens (NFTs) to ensure secure, transparent, and verifiable ticket distribution. The primary aim of the study is to explore how blockchain technology can enhance trust, eliminate fraud, and provide users with full ownership of their tickets. The proposed system employs smart contracts to automate ticket creation, distribution, and resale, thereby minimizing the need for intermediaries. Each ticket is represented as a unique NFT, guaranteeing authenticity and enabling traceability throughout its lifecycle. The methodology involves implementing a decentralized application where event organizers can mint NFT tickets, and users can securely purchase, transfer, or resell them using blockchain infrastructure. The results demonstrate that NFT-based tickets effectively prevent duplication and unauthorized sales while providing an immutable record of ownership. Additionally, organizers gain better control over pricing policies, while buyers benefit from secure transfers and enhanced transparency. In conclusion, this platform contributes to solving long-standing issues in the ticketing industry by combining blockchain’s immutability with NFTs’ uniqueness. The study highlights the potential of decentralized technologies to revolutionize digital ticketing, improve user trust, and create a more efficient event management ecosystem.

Mihaela Gavrilă, Mădălina-Giorgiana Murariu, Delia-Elena Bărbuță, Marin Fotache · 6 authors

This paper presents the design and implementation of a blockchain-secured system for monitoring driver sobriety and real-time geolocation. The proposed platform integrates a Modular Sensor Battery (MSB) for detecting alcohol concentration in exhaled air, a centralized Data Collection Platform (DC Platform) for real-time data visualization and storage, and a complementary physiological monitoring device—the IoT Fit-Bit Smart Band (IFSB)—which captures heart rate and blood oxygen saturation as alternative indicators when breath-based sensing may be compromised. The MSB, the DC Platform, integration with the IoT FitBit Smart Band, and the blockchain-based data management architecture represent the authors’ direct contribution to both the conceptual design and technical implementation. These elements are introduced as part of a unified, fully integrated system designed to enable non-invasive sobriety monitoring and secure data integrity in vehicular contexts. To ensure data authenticity, a custom Ethereum smart contract stores cryptographic hashes of sensor readings, enabling decentralized, tamper-evident verification without exposing sensitive medical information. The system was validated in a controlled experimental environment, confirming its operational robustness and demonstrating its potential to improve road safety through secure, real-time sobriety detection and geolocation tracking.

Mohamed Abdessamed Rezazi, Mouhamed Amine Bouchiha, A. Bendada, Yacine Ghamri-Doudane

Roaming settlement in 5G and beyond networks demands secure, efficient, and trustworthy mechanisms for billing reconciliation between mobile operators. While blockchain promises decentralization and auditability, existing solutions suffer from critical limitations-namely, data privacy risks, assumptions of mutual trust, and scalability bottlenecks. To address these challenges, we present B5GRoam, a novel on-chain and zero-trust framework for secure, privacy-preserving, and scalable roaming settlements. B5GRoam introduces a cryptographically verifiable call detail record (CDR) submission protocol, enabling smart contracts to authenticate usage claims without exposing sensitive data. To preserve privacy, we integrate non-interactive zero-knowledge proofs (zkSNARKs) that allow on-chain verification of roaming activity without revealing user or network details. To meet the high-throughput demands of 5G environments, B5GRoam leverages Layer 2 zk-Rollups, significantly reducing gas costs while maintaining the security guarantees of Layer 1. Experimental results demonstrate a throughput of over 7,200 tx/s with strong privacy and substantial cost savings. By eliminating intermediaries and enhancing verifiability, B5GRoam offers a practical and secure foundation for decentralized roaming in future mobile networks.

Inas Al Khatib, Malick Ndiaye

Bad medical debt negatively impacts individuals' physical and mental well-being, can discourage future care-seeking, and is increasingly viewed as a social determinant of health. Addressing this issue by linking the healthcare sector with humanitarian efforts presents a significant global challenge, requiring innovative solutions. This paper aims to synthesize existing literature on the topic. Using the Scopus database, a systematic review of literature was conducted from 1990 to 2024, employing the PRISMA framework. Thematic analysis was applied to organize and interpret the findings. Reviewing 958 papers, including 318 key sources, revealed a pressing need for a SMART blockchain healthcare platform. Such a platform would securely connect beneficiaries with philanthropists, facilitate data sharing, and align donor requirements with beneficiary criteria. Employing decentralized autonomous organization frameworks and smart contracts ensures transparency, efficiency, and accountability through automated and secure processes.

Chang Liu, Weihua Zhu, Zhongyuan Yao, Xueming Si

Blockchain sharding is a promising approach to improving system scalability. However, traditional designs rely on lock-based cross-shard commit protocols, which introduce significant performance bottlenecks due to repeated on-chain communication and consensus. The emergence of complex cross-shard contracts further exacerbates these issues. Although recent off-chain execution models reduce on-chain overhead by decoupling contract execution from consensus, they still incur high communication costs and struggle to maintain state consistency. To address these challenges, this paper presents a sharding framework that seamlessly integrates on-chain and off-chain processing. By leveraging Trusted Execution Environments (TEEs), the framework enables secure and efficient off-chain execution of cross-shard smart contracts. It incorporates an off-chain execution hub for verifiable contract execution and a state-aware cross-shard commit protocol to guarantee correctness. Furthermore, a genetic algorithm-based contract-migration strategy dynamically reduces cross-shard interactions. Prototype evaluations show that the proposed framework significantly outperforms mainstream sharding solutions, achieving at least 2.1× higher throughput and reducing cross-shard transaction latency by over 52.6%.

Md Bokhtiar Al Zami, Md Raihan Uddin, Dinh C. Nguyen

Federated learning (FL) has gained popularity as a privacy-preserving method of training machine learning models on decentralized networks. However to ensure reliable operation of UAV-assisted FL systems, issues like as excessive energy consumption, communication inefficiencies, and security vulnerabilities must be solved. This paper proposes an innovative framework that integrates Digital Twin (DT) technology and Zero-Knowledge Federated Learning (zkFed) to tackle these challenges. UAVs act as mobile base stations, allowing scattered devices to train FL models locally and upload model updates for aggregation. By incorporating DT technology, our approach enables real-time system monitoring and predictive maintenance, improving UAV network efficiency. Additionally, Zero-Knowledge Proofs (ZKPs) strengthen security by allowing model verification without exposing sensitive data. To optimize energy efficiency and resource management, we introduce a dynamic allocation strategy that adjusts UAV flight paths, transmission power, and processing rates based on network conditions. Using block coordinate descent and convex optimization techniques, our method significantly reduces system energy consumption by up to 29.6% compared to conventional FL approaches. Simulation results demonstrate improved learning performance, security, and scalability, positioning this framework as a promising solution for next-generation UAV-based intelligent networks.

Gabriel Babatunde Iwasokun, Oluwaseyi Segun, Samuel Oluwatayo Ogunlana, Michael Adegoke · 6 authors

The integration of Internet of Things (IoT) devices into modern payment systems has introduced innovative functionalities, but also significant security and performance challenges. IoT devices, such as smart sensors, wearables, and automated vending machines, are typically resource-constrained yet handle sensitive financial transactions that demand robust security mechanisms. Conventional cryptographic solutions are often unsuitable for these environments due to their high computational and memory requirements. This paper presents the design of a lightweight blockchain-based model to secure IoT payment systems by leveraging the Ethereum blockchain and AES-128 encryption. The blockchain token is encrypted with AES-128 to add layer of security before being stored in a database. The model is designed to employ a decentralised digital ledger to record and validate transactions without a central authority, and the transaction is grouped into a block and linked to the preceding block through cryptographic hashes. The chain of blocks forms an immutable record that enhances transparency and security, and the distributed nature of blockchain networks, wherein multiple participants validate each transaction, minimises the risk of fraudulent activities while ensuring consensus is achieved through predefined protocols. Analysis of results from the implementation established the minimization of computational overhead and robust security measures, and was particularly beneficial where the scalability of decentralized systems is required alongside heightened security protocols.

Haruki Kurisaka, Yue Su, Phi Le Nguyen, Kien Nguyen · 5 authors

Abstract The integration of IoT with blockchain technology enhances security and privacy through decentralized, trust-based systems, addressing challenges like single points of failure and limited scalability in traditional IoT architectures. This study evaluates the performance of Ethereum-based IoT systems using resource-constrained devices (Raspberry Pi 4 and Raspberry Pi 3) on a private blockchain. Performance metrics, including CPU, memory, disk usage, power consumption, and latency, were analyzed across three consensus mechanisms: Proof-of-Work (PoW), Proof-of-Authority (PoA), and Proof-of-Stake (PoS). To address the blockchain’s latency performance, we introduced the metrics Transaction-oriented latency (ToL) and Block-oriented latency (BoL) to characterize latency under PoS, capturing the distinctive dynamics of PoS. Our findings show that PoA achieves the lowest resource consumption, with CPU usage reduced by 98% compared to PoW and 20% compared to PoS, and power consumption decreased by 50% from PoW and 14% from PoS. Further, to assess blockchain scalability, we varied transaction transmission rates under PoA, identifying its impact on performance. These findings provide practical guidance for optimizing consensus mechanisms in resource-constrained IoT-blockchain systems.

Giuseppe D’Aniello, Lidia Fotia

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.

Javad Vasheghani Farahani, Horst Treiblmaier

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.

Larissa Tomaz, David R. Matos, Teresa Almeida

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.

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.

Bhabani Sankar Samantray, K. Hemant Kumar Reddy

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.

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.

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.