Advanced connection and autonomous features are being made possible by the Internet of Vehicles (IoV), which is causing a revolution in transportation. Strong security measures are required, however, because the prevalence of connected devices also increases the likelihood of cyberattacks and data breaches. This study introduces a new method for protecting IoV networks, which combines Blockchain technology with Quantum Key Distribution (QKD), creating a security architecture with two layers. Internet of Vehicles (IoV) technologies enable autonomous driving and real-time data exchange by connecting vehicles to infrastructure and one another. These advancements make things safer and more efficient, but they also put sensitive information at risk of cyberattacks. Modern security measures are essential since traditional encryption methods are becoming more and more insecure. To provide encryption that is theoretically unbreakable, the suggested system uses QKD to create and distribute cryptographic keys based on principles of quantum mechanics. To improve trust and transparency, blockchain technology is used to record these keys and any subsequent transactions in an immutable, distributed ledger. A hybrid architecture, with QKD securing the key exchange and Blockchain ensuring the integrity and authenticity of the communication, is designed as part of the integration process. Improved security and speed have been shown in simulations and prototype implementations of the QKD-Blockchain architecture in IoV networks. By preventing eavesdropping and key interception, the QKD technique kept the communication channel secure. With an average delay of only about 2 milliseconds, QKD performed admirably and was well below the permitted range for real-time vehicular communications. On average, validation durations for transactions were 5 milliseconds, which was a little overhead due to blockchain integration. The system efficiently handled up to 10,000 transactions per second without affecting security or performance, proving that it can serve massive IoV networks, according to scalability testing. Under high-load scenarios, the framework maintained consistent performance and security, proving its robustness in stress tests. Together, QKD and Blockchain provide a scalable and trustworthy option for future vehicular communication networks, and these results show how feasible and robust it is to use them to protect IoV systems. An intriguing approach to the security issues plaguing IoV systems is the integration of QKD with Blockchain technology. An unparalleled level of protection against cyber threats is provided by the dual-layered system, which guarantees strong encryption and data integrity. This fresh method may lead to improved and more trustworthy IoV networks by establishing new benchmarks for secure vehicular communication. In order to optimize the implementation and tackle any new issues that may arise, more research and development should be conducted.
Innocent B. Ababio, Jan Bieniek, Mohamed Rahouti, Thaier Hayajneh ¡ 7 authors
Optimizing digital twins in the Industrial Internet of Things (IIoT) requires secure and adaptable AI models. The IIoT enables digital twins, virtual replicas of physical assets, to improve real-time decision-making, but challenges remain in trust, data security, and model accuracy. This paper presents a novel framework combining blockchain technology and federated learning (FL) to address these issues. By deploying AI models on edge devices and using FL, data privacy is maintained while enabling collaboration across industrial assets. Blockchain ensures secure data management and transparency, while explainable AI (XAI) enhances interpretability. The framework improves transparency, control, security, privacy, and scalability for self-optimizing digital twins in IIoT. A real-world evaluation demonstrates the frameworkâs effectiveness in enhancing security, explainability, and optimization, offering improved efficiency and reliability for industrial operations.
Mahmood K. Pathan, J. Rameshkumar, Chintalapudi V. Suresh
The decentralized operation of the power system, which is built entirely on the consensus notion, is one of the most important contemporary subjects in the energy industry. Without the need for a âneutral arbiter, all significant market participants can come to an understanding. Peer-to-peer (P2P) architecture, interface communication, and network security are all discussed in this paper as they pertain to the decentralized nature of the energy market and the paperâs proposed solution: a P2P-based platform. For this reason, it is critical to protect the market playerâs communication interfaces from harmful assaults. In this case, a new blockchain platform coinciding with the P2P energy market ensures that the necessary consensus may be reached safely. An efficient algorithm based on the Relaxed Consensus-Innovation (RCI) protocol controls the energy market, with the goal of facilitating power/price trading between participants in a decentralized, peer-to-peer (P2P) setting. Market participants in the proposed model include a microgrid and a smart grid, both of which are assumed to act in their own self-interest while negotiating with one another in a safe setting. Microgrids use wind turbines, solar panels, tidal turbines, and battery storage units, whereas the smart grid uses distributed generators (DGs) and transmission lines modelled after the IEEE 24-bus test system. In the peer-to-peer energy market, a stochastic framework that is based on unscented transform (UT) has been developed to deal with the uncertainty effects caused by the circumstance. For gauging and validating the fault-tolerant systemâs resistance to cyber-attack, we model and apply the fault data injection attack (FDIA) on the blockchain-based P2P energy marketâ. Simulation results validate the paperâs ideas.
The rapid proliferation of Internet of Things (IoT) networks has significantly advanced various sectors such as smart cities, healthcare, and industrial automation, but it has also introduced substantial security challenges. Protecting data integrity, confidentiality, and availability in these networks is critical, yet traditional security measures often fall short due to the decentralized and resource-constrained nature of IoT devices. The Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol, designed to optimize energy consumption in sensor networks, lacks intrinsic security features. To address these challenges, this paper proposes a novel approach that integrates LEACH with Distributed Ledger Technology (DLT), specifically blockchain. Blockchainâs decentralized and immutable ledger can enhance data security and integrity within IoT networks. The methodology involves modifying LEACH to incorporate blockchain for secure data transmission. In the clustering phase, LEACH forms clusters and designates a cluster head (CH) for data aggregation and transmission. Each CH maintains a local blockchain to log and verify data transactions within its cluster, using a consensus mechanism to ensure data integrity. Smart contracts are implemented to automate security policies and detect anomalies, while data encryption and digital signatures provide additional security layers. Simulations using the NS-3 simulator showed promising results: energy consumption was reduced by 18% compared to traditional LEACH, latency increased by 5% due to blockchain processing overhead, throughput improved by 12%, and security metrics indicated a 25% improvement in data integrity and a 30% reduction in successful attack attempts. In conclusion, integrating the LEACH algorithm with blockchain significantly enhances the security and efficiency of IoT networks. This approach leverages the energy optimization of LEACH and the robust security framework of blockchain, offering a scalable and secure solution for diverse IoT applications. Future research will focus on optimizing blockchain operations to reduce latency further and exploring the model's applicability in various IoT scenarios.
Consensus mechanism is the core technology for blockchain to ensure that transactions are executed in sequence. It also determines the decentralization, security, and efficiency of blockchain. Existing mechanisms all have certain centralization issues and fail to ensure the decentralization of blockchain networks. A decentralized and efficient mechanism is required to improve blockchain systems. This paper proposes a fair consensus mechanism called Proof of Verifiable Functions (PoVF), based on the verifiability and unpredictability of verifiable functions. PoVF provides a sufficiently fair mechanism, ensuring that all nodes in blockchain network have equal opportunity to participate in consensus. In addition, a structure called âDelay bufferâ is proposed to ensure transactions are executed sequentially. It delay the selection of blocks to avoid blockchain forks caused by broadcasting and transaction execution confusion. According to our security analysis, PoVF is provably secure and has the ability to resist potential adversaries. According to the experiments, PoVF-based blockchain can process up to 4 Ă 1 0 3 transactions per second with nodes configured with only 4-core CPUs. This paper uses the Gini coefficient to measure the decentralization of blockchains, and the PoVF-based blockchain achieves the lowest Gini coefficient of 0.39 among all sampled blockchains. PoVF has been shown to provide sufficient efficiency while ensuring decentralization and security through experiments.
Amit Kumar Sharma, L. Ganesh Babu, Mrunalini Buradkar, M. Shanmathi ¡ 6 authors
PURPOSE: With a focus on enhancing transparency, lowering the risk of fraud, and ensuring ethical sourcing practices, this research aims to investigate how blockchain and IoT technologies can be incorporated into the diamond supply chain. This study addresses the complexities and challenges of implementing these technologies in an industry characterized by fragmented information sharing and centralized data storage. DESIGN/METHODOLOGY/APPROACH: Using both qualitative and quantitative analysis, the research uses a mixed-methods approach. While secondary data was obtained from previously published works, industry reports, and case studies, primary data was gathered through semi-structured interviews with professionals in the field. The implementation of the prototype system was carried out in three phases: Define, Operate, and Test. Ethereum was chosen for its smart contract capabilities, and various IoT sensors were deployed to monitor environmental conditions and track the real-time location of diamonds. FINDINGS: The integration of blockchain and IoT technologies significantly enhanced transparency within the diamond supply chain. The immutable nature of blockchain ensured tamper-proof records of transactions, while IoT sensors provided continuous real-time data, reinforcing transparency. The study observed a notable reduction in fraud due to the robust mechanisms of the system, which detected and prevented unauthorized alterations to the recorded data. Smart contracts automated compliance checks, ensuring adherence to ethical standards. Quantitative analysis revealed improvements in key metrics such as fraud reduction rates, transparency enhancements, and adherence to ethical sourcing standards. ORIGINALITY/VALUE: This study bridges a notable gap in existing research by focusing on the diamond supply chain. It provides comprehensive, data-driven insights and practical recommendations for industry stakeholders and policymakers. The results highlight how combining blockchain and IoT technology can improve operational efficiency, transparency, and ethical practices in the diamond business. It is also feasible and scalable. The study's methods and findings add a great deal to the body of information already in existence and provide a framework for further investigation and application in related situations.
Zia Ullah, Ghassan Husnain, Abid Iqbal, Ibrar Ali Shah ¡ 8 authors
ABSTRACT Vehicular adâhoc networks (VANETs) are pivotal in intelligent transportation systems (ITS), enabling enhanced traffic efficiency and safety. However, VANETs within ITS face critical challenges related to trust, privacy, and data reliability. To address these issues, this paper proposes a comprehensive solution that integrates blockchain and InterPlanetary file system (IPFS) technologies for ITS applications. We introduce a blockchainâbased trust management system, TrustChainâVANETs, designed to ensure message credibility, privacy, and data reliability in ITS environments. Our model safeguards vehicle privacy while enabling credible messages to be shared through anonymous aggregate vehicular announcements, an essential feature for ITS. Reputation values, stored in the blockchain, allow roadside units (RSUs) to assess message reliability, achieving a 15% higher malicious vehicle detection rate compared to traditional methods at low probabilities of false reporting, crucial for trust in ITS. Additionally, conditional privacy is maintained by tracking malicious entities through public addresses, ensuring accountability in ITS. The system leverages IPFS on RSUs for secure, reliable data storage, with aggregated event data from vehicles stored in IPFS and vehicle reputation values maintained on the blockchain, addressing storage and cost challenges in ITS. This approach reduces transaction costs by 20% and decreases storage overhead by 30%, enhancing the efficiency of ITS data sharing. An incentive mechanism encourages honest data sharing among vehicles, with monetary rewards for aligning with verified event information, transparently recorded on the blockchain. Performance analysis demonstrates that TrustChainâVANETs reduces message verification time by an average of 25% compared to traditional proofâofâwork blockchain models, making it suitable for the dynamic and demanding nature of ITS. This innovative framework addresses critical challenges in VANETs, delivering robust, scalable, and efficient solutions for security, privacy, and reliability in ITS.
Uncrewed aerial systems (UASs) were popularly used by hobbyists in the past, but they have now become critical enablers for managing disasters, handling emergencies, and so on. For example, one of their most critical applications is to provide seamless wireless communication services in remote rural areas. Thus, it is substantial to identify and consider the different security challenges in the research and development associated with advanced UAS-based B5G/6G architectures. Catering to this requirement, this article conducts a comprehensive review of the security aspects of UASs with respect to the 5G/6G system architecture, its enabling technologies, and privacy issues. It exhibits security integration at all the protocol stack layers and analyzes the existing mechanisms to secure UAS-based B5G/6G communications and its energy and power optimization factors. Last, this article also summarizes modern technological trends for establishing security and protecting UAS-based systems, along with the open challenges and strategies for future research work.
Khadija Tlemçani, Kebira Azbeg, El Mehdi Saoudi, Leila Fetjah ¡ 6 authors
In the evolving landscape of health information management, the application of blockchain and edge computing technologies to chronic disease management remains underexplored, despite the urgent need for scalable, secure, and real-time solutions. This systematic review examines the integration of these technologies in healthcare, with a specific focus on diabetes management. We analyzed 52 studies, categorizing findings into three key areas: enhanced data security and privacy through decentralized frameworks and tamper-proof storage; real-time data processing, enabled by edge computing for immediate analytics and alerts; and scalability, achieved via hybrid architectures that optimize data handling. Our review identifies critical gaps in the existing literature, particularly the lack of tailored approaches for chronic disease contexts like diabetes, and outlines future directions for developing robust, secure, scalable, and real-time data solutions. This study provides a foundation for innovation in healthcare technology that can significantly impact diabetes care and chronic disease management.
N. Sethu Subramanian, Prabhakar Krishnan, Kurunandan Jain, K. B. Aneesh Kumar ¡ 6 authors
5G (Fifth Generation) technology represents a significant advancement in telecommunications, facilitating industry innovation and advancement for applications across various sectors. It enhances high-speed, low-latency communication, making it ideal for task offloading in resource-constrained mobile devices. By leveraging task offloading, 5G networks maximize the efficiency of both computational and network resources, ensuring faster, more reliable data delivery and enabling high-performance requirements of modern applications. However, dynamic and secure task offloading remains a challenge due to fluctuating network conditions and trust concerns. This paper proposes SAGE (Secured Adaptive Generalized Edge), a reinforcement learning-based task offloading framework that leverages contextual bandits for adaptive decision-making in Multi-Access Edge Computing (MEC) environments. By integrating blockchain smart contracts for security and SDN-based orchestration for dynamic resource management, SAGE ensures robust, low-latency offloading. Experimental evaluations demonstrate that SAGE reduces task offloading delays by 36% and task durations by 30% compared to baseline methods under varying load and energy constraints.
Data security and privacy are crucial for the Internet of Medical Things (IoMT) and the digitization of healthcare systems. IoMT offers a revolutionary approach to healthcare monitoring, enabling remote patient interaction, sensor data collection, and even in-body implants. However, its wireless nature creates significant security vulnerabilities, and robust security mechanisms are essential to ensure patient trust. Hence, a lightweight privacy preservation mechanism based on blockchain and consensus is developed with minimal computational overhead. Initially, the reputation score is computed for every registered node using the confidence threshold value and transaction to verify the trustworthiness of the IoMT nodes. Tiny Feistel Cipher Encryption technique (TFCEA), a lightweight cryptographic technique, has been proposed to encrypt IoMT data. Based on the computed trust score, an Adaptive Proof of Work (APoW) consensus algorithm has been used to regulate block creation. APoW implements the Genetically Modified Salp Swarm Optimization (GM-SSO) algorithm for the node selection. To make it lightweight, the experimentation used the lightweight cryptographic algorithm and fine-tuned consensus APOW to facilitate the addition of new blocks according to their trust score. In terms of performance analysis, the presented experiments are benchmarked with the well-established works in the candidate domain. Tested results reveal its economic affordability by attaining 243.513 ms for 500 records as an execution time. An informal security analysis has been carried out to justify the robustness of the presented framework against various attacks. To increase resilience against cyber-attacks and ensure reliability in healthcare data security, Modified Principal Component Analysis (MPCA) enabled anomaly detection models were built using the BoT-IoT dataset. Tested models achieve 99.99% and 98.75% accuracy, indicating that the developed model is more suitable to prevent the possible cyber-attacks anticipated in smart healthcare.
Mozhgan Gholami, Ali Ghaffari, Nahideh Derakhshanfard, Nadir iBRAHIMOÄLU ¡ 5 authors
The Internet has been enhanced recently by blockchain and Internet of Things (IoT) networks. The Internet of Things is a network of various sensor-equipped devices. It gradually integrates the Internet, sensors, and cloud com... | Find, read and cite all the research you need on Tech Science Press
With the rise of the internet of things (IoT), ensuring operational efficiency and security for resource-constrained nodes has become crucial. This paper proposes two certificate-less key agreement protocols based on confidential message entanglement, addressing limitations of traditional key management such as certificate reliance and high computational costs. A smart contract-driven, dynamically switchable distributed key management framework is also introduced to enhance adaptability under varying attack frequencies. Simulation results indicate reduced communication and computational overhead. Protocols 1 and 2 show computational losses of 5.53 and 6.47, respectively, while smart contract-based scenarios range from 4.28 to 4.39. In smart agriculture applications, dynamic switching reduced overhead from 6.47 to 4.28, optimising performance by 33.84%. The research supports the development of lightweight, secure, and adaptable communication frameworks for IoT applications in smart cities, industrial monitoring, and telemedicine, offering strong theoretical and practical value.
With the rapid expansion of the Internet of Things (IoT), the integrity of connected devices has emerged as a critical concern. Malicious actors increasingly target vulnerabilities in device firmware, communication protocols, and system configurations, compromising the reliability and trustworthiness of data. Traditional security mechanisms have struggled to scale with the decentralized and heterogeneous nature of IoT networks. To address this challenge, this paper proposes a blockchain-based framework designed to safeguard the integrity of IoT devices. The framework leverages a lightweight consensus mechanism and a distributed ledger to establish tamper-evident records of device behavior and configuration states. Additionally, smart contracts are employed to automate verification processes, detect anomalies, and enforce compliance with integrity policies in real time. The case study conducted demonstrates how this approach enables secure attestation of device states while minimizing computational overhead, making it suitable for resource-constrained environments. The proposed framework represents a step forward in embedding trust into the fabric of IoT systems through decentralized integrity assurance mechanisms.
Industry 4.0 has accelerated the adoption of the Industrial Internet of Things (IIoT), enabling intelligent communication among industrial devices, edge systems, and cloud platforms for smart manufacturing. However, conventional centralized security approaches are increasingly vulnerable to cyber threats, data tampering, and single-point failures. This paper proposes a secure blockchain-enabled IIoT architecture that integrates industrial sensing, edge computing, distributed ledger technology, cloud analytics, and intelligent decision-making. The framework employs device authentication, encrypted communication, decentralized consensus, smart contracts, and machine learning-based anomaly detection to enhance data integrity, secure information sharing, and cyber resilience. Experimental evaluation demonstrates improvements in communication security, authentication accuracy, transparency, scalability, latency, and throughput, making the proposed architecture a robust and scalable solution for secure next-generation smart engineering and industrial automation.