The research proposes and evaluates a blockchain-based AIoT inspection system implemented on an NVIDIA Jetson Xavier NX edge computing device. The system integrates AI-powered inspection capabilities with Hyperledger Fabric blockchain technology to ensure tamper-proof record-keeping and data integrity. Performance analysis demonstrates the feasibility of running distributed ledger technology in conjunction with AI processing on edge computing devices. The implementation achieves reliable verification of inspection data while maintaining acceptable computational resource usage and energy consumption. Results indicate that blockchain integration prevents unauthorized data manipulation without significantly compromising system performance.
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.
Yassine Maadallah, Younès El Bouzekri El Idrissi, Youssef Baddi
Blockchain technology offers a promising foundation for trustworthy, auditable communication in Internet of Things (IoT) networks. In such settings, the consensus protocol is the primary determinant of feasibility because devices operate under tight constraints in energy, computation, latency, and bandwidth. This paper delivers a structured comparative review of Proof of Work (PoW) and Proof of Stake (PoS) in the context of IoT. We first articulate their operating principles, security assumptions, and threat models, then evaluate trade-offs across throughput, latency, scalability, energy consumption, hardware requirements, and attack resistance. While PoW provides strong probabilistic finality and robust security under open membership, its high energy cost and mining difficulty make it poorly aligned with low-power sensor/actuator nodes. PoS and PoS-inspired variants reduce resource use and enable faster confirmation, but require careful design to mitigate concentration risks, long-range and nothing-at-stake attacks, and to preserve decentralization. Beyond these canonical schemes, we review emerging alternatives tailored to IoT, including lightweight PoW, committee-based BFT hybrids, and DAG-based ledgers that decouple consensus from transaction validation. We synthesize implementation considerations, including identity and stake management, clock synchronization, network churn, and intermittent connectivity, and outline selection guidelines for common IoT deployment patterns (edge-centric, gateway-assisted, and intermittently connected swarms). Our analysis indicates that PoS and related frameworks are generally better suited for IoT, particularly when combined with hierarchical or hybrid designs. The review concludes with open research directions and a pragmatic checklist for researchers and practitioners evaluating consensus for constrained IoT systems.
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.
Anurag Shrivastava, RVS Praveen, Mohammed I. Habelalmateen, Arti Badhoutiya · 6 authors
The integration of blockchain technology with the Internet of Things (IoT) and Industrial Internet of Things (IIoT) heralds a transformative era for numerous industries by enhancing security, ensuring data integrity, and fostering trust through decentralized mechanisms. This comprehensive survey explores the convergence of blockchain solutions within IoT and IIoT frameworks, highlighting the technological advancements, security challenges, and potential attacks that characterize this evolving landscape. By scrutinizing various blockchain architectures, consensus mechanisms, and real-world applications alongside a critical examination of security threats including DoS, fuzzers, and combined assaults, the study offers an in-depth understanding of both the potential and the pitfalls of blockchain in IoT and IIoT contexts. Through analyzing performance metrics against attacks and discussing mitigation strategies, this survey aims to provide a roadmap for researchers, practitioners, and policymakers to navigate the complexities of securing blockchain-enabled IoT and IIoT systems.
The accelerated growth of IoT devices creates new problems about protecting data while assuring ethical standards and reducing power requirements. The authors present DPASS as a security scheme that unites SDN and blockchain technology to secure IoT networks and simultaneously reduce power consumption. The Energy-Aware Secure Chain algorithm within the proposed framework combines three operational mechanisms including the FEP for quick node-validation and SZPM for minimal-resource data transmission and Secured Spatial Storage and Query for secure data integrity. The system leverages IBM Watson IoT and Ethereum blockchain for implementation and evaluation. The proposed model exhibits superior results compared to existing products regarding both execution speed and authentication strength with better computational capability and power efficiency metrics. The experimental results show that DPASS establishes strong network security without wasting excessive resources thus providing an excellent solution for secure IoT deployment. The research achieves architectural advancement for robust IoT systems through a combination of SDN-based automation with blockchain’s unalterable security elements which ensures reliable device connectivity.
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.
Li Xingchen, Zhou Zhang, Burra Venkata Durga Kumar
One of the most important properties of cold chain is that ensure that temperature-sensitive products such as food, medicine, and chemicals maintain quality and safety during transportation and storage. For traditional cold chain systems, most operations such as transportation and inspection were relying on manual inspection and decentralized systems, which are inefficient, error-prone, and lack transparency. Today, some studies have combined blockchain technology with the Internet of Things (IoT) to store various necessary supply chain data on the blockchain, thereby achieving the role of monitoring and review, providing a basic solution to these challenges. But there still some problems, for example, how to attribute the responsibility in the transportation process to individuals to achieve a precise accountability system? For example, know who is responsible for this leg of the shipment? who is responsible for receiving this shipment? Since the temperature and humidity data of the fruit may be constantly changing, how can you effectively detect whether these changes are justified so that you can respond effectively and in a timely manner to irregularities? Regarding above mentioned issues, in this paper, we propose a two-tier framework that combines biometric-based Zero Knowledge Proof (ZKP) authentication and AE-based AI anomaly detection. The authentication subsystem uses biometric data and personal information to generate credentials, which are verified by the ZKP stored on the chain. Meanwhile, the IoT device collects multisource sensor data processed by feature engineering, and detects temperature, humidity, and route anomalies via VAE model.
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.
The acceleration and widespread application of wireless networks underscore the pressing need for innovative solutions in wireless resource management, with blockchain emerging as a transformative approach due to its decentralized and secure nature. Our paper provides a panorama of blockchain-driven wireless resource management and emphasizes critical aspects such as spectrum utilization, infrastructure sharing, and interference management. We analyze representative models, including optimization, game model, auction mechanism, and machine learning, with mathematical formulations for a deeper understanding of blockchain’s impact. These methodologies underpin flexible and adaptive resource allocation strategies tailored for dynamic and high-demand environments. Recognizing the challenges of integrating blockchain with wireless networks, on the one hand, we investigate advanced blockchain solutions at both Layer 1 and Layer 2 that enhance scalability and adaptability for large-scale networks. On the other hand, we also exploit networking technologies, such as virtualization, network slicing, etc., to ensure seamless compatibility with blockchain. Furthermore, through several typical application scenarios, our paper illustrates the adaptability and practical benefits of blockchain in next-generation wireless networks. At last, this survey offers significant insights into blockchain’s role and potential in the evolution of wireless communication and outlines future research directions to facilitate a seamless transition to 6G.
Na Wang, Yaning Wang, Jianwei Liu, Junsong Fu · 5 authors
In the development of urban transportation, Intelligent Connected Vehicle (ICV) technology has become a key force in promoting intelligence, sustainability, and efficiency. In particular, the rapid development of electric vehicles (EVs) has led to a growing demand for charging. However, this process risks exposing the private payment information of EV users, including the location of charging stations, the moment of charging, and users' identities. Our paper proposes a blockchain-based distributed privacy-preserving payment scheme named “SecretCharge”, designed to protect users' private information for ICV payment service scenarios. To meet the demands of large-scale applications of ICV, we propose an efficient group signature scheme based on the ElGamal signature, achieving high efficiency in key generation, signing, and verification algorithms. To conceal the payment information of EV users, we sign the data using our group signature scheme and use it as input for a zero-knowledge proof, ensuring that the information can be verified without being disclosed. To eliminate the dependence on third-party billing entities in traditional centralized schemes, we process system payments on the blockchain, achieving decentralization. Finally, our scheme is tested on Ethereum. The experimental results demonstrate our scheme's efficiency and usability, achieving privacy protection for user payment information in ICV.