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 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.
The implementation of Industrial Internet of Things (IIoT) is significantly constrained by the emergence of Data security. This paper examines the primary data security issues and protection mechanisms associated with IIoT, providing a comprehensive analysis of how security protection systems evolve across the stages of data collection, transmission, storage, and processing. The focus is directed towards advancements in edge computing and lightweight distributed ledger technologies, which significantly enhance data security. The paper begins with a review of the evolution and development of IIoT, highlighting the challenges that current technologies present in effectively addressing data privacy, integrity, real-time performance, and scalability. Following this, the analysis focuses on the efficacy of edge computing to mitigate data exposure while simultaneously improving computational efficiency. Additionally, the study examines the benefits of lightweight distributed ledger technologies for resource-constrained environments, highlighting their role in ensuring data immutability and enhancing data transparency. The paper concludes by analyzing potential trends in IIoT data security technologies, such as post-quantum cryptography, AI-driven security protections, and zero-trust architectures, and by offering perspectives on the future of technological advancements.
In security and resilience, another vital issue is to maintain the secure and robust RF communication in Industrial Internet of Things (IIoT) settings in which the use of multiantenna systems is constrained by physical implausibilities.The current paper is a proposal of a Blockchain-Enhanced Secure RF Link Transmission (BESRFT) scheme targeting antennaconstrained IIoT applications.The framework for those aspects integrates adaptive tuning of the RF parameters with a lightweight blockchain distributed consensus protocol that restores assuring and even securing communication in event of a cyber-physical assault condition.The proposed structure combines a modified Proof-of-Authentication (PoA) consensus mechanism that scales well and has low overheads to communicate across the IIoT nodes via an edge and smart contracts are used to authenticate the devices, negotiate the session keys and record intrusions on the fly.To critical hardware constraints, the system dynamically adjusts transmission parameters e.g.frequency, modulation and power depending on real-time channel metrics e.g.RSSI and SINR resulting in a low degree of information loss and power overhead.The simulation results based on the tool NS-3 and Hyper ledger Besu prove the effectiveness of BESRFT as it provided a spoofing detection rate of 97.6 percent that lessened packet drop rates by 66 percent or 18.2 to 5.1 percent, and decreased jamming recovery time by 66 percent or 1.8 seconds to merely 0.6 seconds.Additionally, the validation of prototype approaches that involve TI CC2652R1 and STM32 microcontrollers also confirms that the latency (~1.2 s) and memory overhead (<5%) of blockchain synchronization are minimal, thus confirming that the solution is suitable to be deployed in the resource-constrained IIoT environments.The combined architecture does not only improve commanding situation but also increases the efficiency of an industrial system like smart grid, oil refineries, and factory automation platforms.The piece instates a decentralized trust system with the RF protection link without requiring the complicated cryptographic infrastructures and centralized control.In the future, the framework has a great potential to be scaled to reconfigurable metasurface-based antenna systems and reconfigurable IIoT architectures with 6G-enabling properties, where the secure, low-latency, and adaptive communication will play a fundamental role.
Integrating blockchain with IoT ensures secure, transparent data exchange through immutability and consensus mechanisms, preventing data tampering. However, the increasing number of IoT devices raises risks like unauthorized access and network attacks. Blockchain scalability issues also affect throughput and latency, challenging real-time IoT applications. This thesis addresses these challenges through four contributions that aim to improve the security, scalability, and efficiency of blockchainbased IoT networks, balancing security with performance needs. Our first contribution is to develop an end-to-end security mechanism for IoT networks, called the trust-based ABAC mechanism for IoT networks (TABI). TABI integrates edge computing and blockchain technology to mitigate risks from malicious devices and offload computational tasks to edge layers. It operates on Hyperledger Fabric (HLF), a permissioned blockchain that enhances throughput and latency through its executeorder- validate architecture. Our second objective is to provide scalability within blockchain-based IoT networks using a sidechain-based trust and access control system, named sidechain-based trust and access control mechanism for IoT networks (SATI). By distributing trust evaluation and access control operations across a separate blockchain or sidechain, SATI improves the scalability of IoT networks. We implement a cross-chain transfer mechanism to ensure communication between the sidechain and the mainchain, thus overcoming a fundamental limitation of traditional blockchain architectures. Our third contribution is to improve the security of the IoT network by introducing a Zero-Knowledge Proof-based Mutual Authentication (ZPMA) mechanism, a privacy-preserving mutual authentication mechanism. Utilizing Zero-Knowledge Proofs (ZKP) based on the quadratic residue technique, Z-PMA ensures secure and private mutual authentication between edge devices and IoT devices. We also implement an incentive mechanism to select additional authenticators from the base station layer to reduce authentication latency and support the demands of low-latency IoT networks. Our fourth contribution is to detect and resolve conflicting transactions in HLF-based IoT networks at an early stage, known as the early-stage conflict transaction resolution (ECR) mechanism. ECR identifies and resolves conflicting transactions at an early stage using a local cache at the endorsement phase of the HLF transaction processing. Additionally, ECR uses dependency model and an efficient reordering process to distribute transactions in a way that minimizes conflicts. This mechanism enhances the performance of HLF-based IoT networks by reducing the impact of conflicting transactions, ultimately improving throughput and latency.
The adoption of the Internet of Things in critical applications highlights the need to strengthen security in its perception layer, one of the most vulnerable. This article presents a threat model for this layer, identifying replay, denial-of-service, and network traffic capture attacks as the most critical. In order to counteract them, an optimized variant of an authentication protocol based on zero-knowledge proofs is proposed, improving the efficiency and scalability of the original Hecht protocol. The solution introduces elementary matrices to reduce protocol computational complexity and an explicit mechanism for secure secret management. It is experimentally validated in a QR code-based access control system, simulating a real Internet of Things environment. The results show that the proposed variant is lightweight, efficient, and suitable for resource-constrained devices, especially in web environments, offering a high level of security by not revealing information about the secret key during authentication. Furthermore, a design of experiments optimizes the protocol parameters, minimizing execution time without compromising security. The proposed protocol represents a significant improvement in security and efficiency for authentication in the Internet of Things perception layer.
Mohammad Iqbal Saryuddin Assaqty, Ying Gao, Abeer D. Algarni, Siraj Khan · 7 authors
The complexity of the entire process of supply chain management (SCM) is quite cumbersome and traditional way of handling it is devoid of proper authentication and security and very often suffers from human errors in dealing with flaws in quality control process of SCM. While it may have started with shipment tracking, the outcome of using IoT on supply chains has spread to every link in the chain. For instance, manufacturers are employing Internet-enabled sensors in production to find product faults, resulting in higher-quality production runs. Physical Unclonable Function (PUF) is a security mechanism that exploits the unique, unrepeatable physical characteristics of hardware components to generate distinct cryptographic keys or identifiers, typically for a semiconductor device like an Internet of Things (IoT) device. The unique identification of IoT devices along the supply chain is implemented by using PUFs as tamper-resistant IDs. Blockchain, the distributed, immutable ledger, on the other hand is the disruptive technology that provides higher security as compared to traditional centralized systems. The integration of PUF and blockchain proves to be quite interesting while handling the above issues of authentication. A smart contract on the blockchain is a software code that executes spontaneously as and when the conditions of the contract or agreement are satisfied. Hence after authentication process the results are fed to blockchain smart contract for the final validation. This paper presents a novel permissioned blockchain smart contract-based lightweight authentication scheme for SCM using PUF of IoT known as SPUFChain. Informal and formal security analysis (using AVISPA and BAN logic) of the proposed framework show its potential to combat several attack scenarios like man-in-the middle, non-repudiation, impersonation, replay attacks and many other security features as compared to other related schemes. The processing time (~13.8ms) is better than existing lightweight scheme for blockchain-based SCM as well.
Most existing research on decentralized IoT applications tends to address specific vulnerabilities, with relatively few techniques dedicated to managing privacy and trust issues. To mitigate these challenges, blockchain-based solutions are increasingly adopted to enhance the reliability and security of IoT networks. In particular, blockchain-based authentication frameworks offer a decentralized approach to storing and verifying device identities, enabling secure and trustless communication among devices and with external systems. However, current blockchain-based IoT systems often suffer from complexity and storage overhead. To address these limitations, we propose a novel solution tailored for large-scale IoT environments using a permissioned blockchain. Our approach incorporates optimized data storage and a lightweight authentication mechanism, offering improved scalability and reduced storage demands. Furthermore, we introduce, for the first time, the integration of homomorphic encryption to secure IoT data at the user end before uploading it to the cloud. The proposed framework is evaluated through comprehensive simulations and compared with existing benchmark models. This research contributes a trust-aware security model that significantly enhances both the privacy and security of IoT services.
Open access
Blockchain Technology Applications and Security
IoT and Edge/Fog Computing
Advanced Steganography and Watermarking Techniques
The growth of the Metaverse brings new security problems that traditional perimeter-based defenses canât manage. This research proposes and tests an integrated Zero-Trust Architecture aimed to solve these weaknesses by merging artificial intelligence (AI)-driven behavioral threat detection, blockchain-based decentralized identification, and post-quantum cryptography. For anomaly detection, the architecture uses a federated ResNet-50 model; for data management that meets regulatory standards, it uses a Hyperledger Fabric-based identification system with Zero-Knowledge Succinct Non-Interactive Argument of Knowledge; and for key exchange that is immune to quantum attacks, it uses the CRYSTALS-Kyber algorithm. Penetration testing, a Delphi study with 20 experts, and user surveys all show that the architecture greatly improves security metrics. This system has a False Acceptance Rate (FAR) of 5.2%, which is 42.7% lower than the 9.1% FAR baseline of rule-based systems, 99.1% protection against Sybil attacks, and strong quantum resilience with a 1.2Ă latency penalty compared to AES-256. The approach also partially complies with the General Data Protection Regulation by using cryptographic erasure proofs. But these security improvements come at a cost: AI inference now uses 3.1 times more graphics processing unit resources. The results show that the suggested architecture creates a scalable, empirically validated basis for protecting decentralized virtual environments, striking a good balance between security, compliance, and performance trade-offs.
Smart home technologies have revolutionized modern living by enhancing convenience, efficiency, and security. In contrast, many interconnected devices introduce significant security and privacy challenges. This comprehensive review investigates the integration of blockchain technology as a robust solution for secure access control in smart home environments. The decentralized and tamper-resistant nature of blockchain technology effectively solves important problems, including device authentication, data integrity, and access management, through the use of cryptography and distributed ledgers. The study synthesizes findings from 52 research papers, categorizing them into three thematic areas: blockchain in access control systems, its applications in IoT, and specific implementations for smart homes. It highlights the transformative potential of blockchain in mitigating vulnerabilities inherent in centralized systems, fostering trust, and enhancing security frameworks. Despite its promising applications, challenges such as scalability, interoperability, and energy consumption persist, warranting further research. This paper stresses the necessity of collaboration to tackle these limitations and enhance blockchain-based access control solutions for smart homes, setting the stage for more secure and user-focused smart environments.
The rapid growth of the metaverse has led to a scattered ecosystem in which digital assets are deployed on different blockchain platforms. This disintegration creates significant challenges for interoperability, as users need secure, decentralized, and privacy-preserving protocols to enable interoperability between chains. Existing solutions typically depend on centralized exchanges or third-party relays, introducing a single point of failure and potential privacy risks. We propose MAM (Metaverse Asset Management), a novel user-centric protocol utilizing zkSNARK technology (Zero-Knowledge Succinct Non-Interactive Argument of Knowledge) that enables seamless movement of metaverse assets across various blockchain platforms. MAMâs architecture ensures privacy by generating all zkSNARK proofs locally on the userâs machine, ensuring that sensitive data, including private keys and asset metadata, never leave the device. The protocol employs a secure one-time setup to distribute the global circuit-specific proving key, ensuring the permanent destruction of toxic-waste data. Experimental evaluation demonstrates that MAM achieves a constant and minimal proof size (192 bytes), low gas cost (281,107 Gas per verification), and an end-to-end asset transfer latency under 15 seconds, outperforming recent alternatives such as MetaOpera and MAP. Static security analysis confirms the robustness of MAMâs smart contracts against the most significant vulnerability types. This research enhances the state-of-the-art of privacy-preserving and scalable cross-metaverse interoperability, providing a practical approach for fully decentralized digital asset management and transfer across the Metaverse.