With the further expansion of 5G networks, a main priority continues to shift towards secure and efficient protocols for data transmission. Traditional 5G security mechanisms, such as 3GPP AKA protocols, have limitations in scalability, latency, and resilience against cyber threats, making them quite unsuitable for complex high-density 5G environments. This study proposes a Secure Blockchain-based Data Transmission Protocol (SBDTP) with the decentralized and tamper-resistant feature of blockchain, combined with a hybrid consensus mechanism driven by Proof of Stake (PoS) or Practical Byzantine Fault Tolerance (PBFT). In this respect, this study contributes to state-of-the-art research efforts in the field of enhancing data integrity, authentication, and confidentiality with reduced latency and energy consumption in 5G applications. Extensive simulations showed that SBDTP outperformed previous solutions by a large margin. This protocol reduces latency to 50-80 ms, increases throughput to 900 pps, allows up to 1000 nodes without performance degradation, and reduces energy consumption to 0.8 J per node. It also maintains a very close-to-perfection data integrity check rate of ~100% and a very minimal privacy loss rate of less than 1%, showing strong security that could serve well for real-time 5G applications such as IoT networks, autonomous vehicles, and smart cities. These results show that SBDTP offers an efficient and secure solution for data transmission over 5G networks, outperforming traditional and blockchain-based methods while fulfilling the tight requirements posed by next-generation networks. In the future, the protocol should be optimized for scalability, including further advanced privacy techniques to widen its adaptability to diverse 5G applications.
ABSTRACT The rapid evolution of the Internet of Things (IoT) has revolutionized various sectors, fostering seamless intercommunication and real‐time monitoring. Central to this transformation is integrating blockchain technology, which ensures data integrity and security in IoT networks. This paper provides a meticulous exploration of data aggregation techniques within the context of blockchain‐based IoT systems. The study categorizes data aggregation algorithms into Privacy‐Preserving, Machine Learning‐Based, Hierarchical, Real‐Time, and Custom Aggregation Algorithms, each tailored to specific IoT requirements. Privacy‐Preserving Aggregation Algorithms focus on safeguarding sensitive data through encryption and secure protocols. Machine Learning‐Based Aggregation adapts dynamically to data patterns, offering predictive insights and real‐time adaptability. Hierarchical Aggregation organizes devices into a structured hierarchy, optimizing data processing. Real‐Time Aggregation processes data instantly, ensuring low latency for time‐sensitive applications. Custom Aggregation Algorithms are bespoke solutions tailored to unique application demands, emphasizing efficiency and security. Through a comparative analysis of these techniques, this paper explores their advantages, disadvantages, and applicability, addressing the challenges and suggesting future research directions. The integration of blockchain‐based data aggregation techniques not only enhances IoT network efficiency but also ensures the longevity and security of modern technological infrastructures. This study builds upon prior research in the field of IoT and blockchain technology by extending the exploration of data aggregation techniques and their implications for network efficiency and security. SLR method has been used to investigate each one in terms of influential properties such as the main idea, advantages, disadvantages, and strategies. The results indicate most of the articles were published in 2021 and 2022. Moreover, some important parameters such as privacy and security, latency, data processing, energy consumption, complexity, and reliability were involved in these investigations.
Scalability and automation in “Industrial Internet of Things (IIoT)” aims to improve productivity in smart factory setting. For scalability, protection, collaboration, optimization, and automation in industry, smart systems, Internet of Things (IoT), and information and communication technologies (ICTs) are integrated as an individual organism. This study proposes a safe data-sharing system based on blockchain to provide security in industry with IoT. As per blockchain’s reputation, end-to-end authentication is developed and smart contract can validate security measures of nodes. With categorization and integrity verification in industry and node terminals, the paradigm of blockchain manages dissemination and data collection. The “Proof of Authentication (PoAh)” is a consensus mechanism developed with blockchain network to develop a collaborative network for retaining verification and log data in IIoT. It achieves tracing of endpoint activity and trusted authentication. Blockchain nodes also uses edge computing to provide authentication of devices using PoAh and smart contracts. The proposed architecture achieves high response rate and cuts the time for authentication. The service time in the proposed system shows efficiency of blockchain system for IIoT in comparison to current works. Finally, several block sizes were evaluated for efficient transaction.
Juan Minango, Henry Carvajal Mora, Marcelo Zambrano, Nathaly Orozco Garzón · 5 authors
This paper evaluates the technical feasibility of Distributed Ledger Technology (DLT) within the healthcare ecosystem, with a focus on the use of Corda DLT to enhance governance and performance in a decentralized ecosystem, ensuring data integrity, security, and trustworthiness. Key attributes examined include the guarantee of data integrity, ensuring that transmitted data remain unaltered; authenticity through the implementation of digital signatures and certificates; confidentiality achieved via secure peer-to-peer communication accessible only to authorized parties; and traceability and auditing mechanisms that enable tracking of information changes and accountability. To validate these features, a Corda Distributed Application (CorDapp) was developed to manage the core logic of the healthcare ecosystem. The CorDapp was deployed across nodes and executed within the Corda network. Its performance was assessed using metrics such as throughput, latency, CPU usage, and memory consumption in both local and cloud network environments. Results demonstrate the feasibility of using Corda DLT technology in healthcare, effectively addressing critical requirements such as integrity, authenticity, confidentiality, traceability, and auditing while maintaining satisfactory performance across diverse deployment scenarios.
Aiming to address the shortcomings of traditional blockchain technologies, characterized by high storage redundancy and low transaction query efficiency, we propose a lightweight sender-based blockchain architecture (LSB). In this architecture, the linkage between blocks is associated with the user initiating the transaction, and the hash of the newly generated block is recorded in the user’s wallet, thereby facilitating transaction retrieval. Each user node must store only the blocks that pertain to it, significantly reducing storage costs. To ensure the normal operation of the system, the Delegated Proof of Stake based on Reputation and PBFT (RP-DPoS) consensus algorithm is employed, establishing a reputation model to select honest and reliable nodes for consensus participation while utilizing the Practical Byzantine Fault Tolerance (PBFT) algorithm to verify blocks. The experimental results demonstrate that LSB reduces storage overhead while enhancing the efficiency of querying and verifying transactions. Moreover, in terms of security, it decreases the likelihood of malicious nodes being designated as agent nodes, thereby increasing the chances of honest nodes being selected for consensus participation.
The proliferation of Internet of Things (IoT) devices in smart environments has created unprecedented challenges in identity management and security. Traditional centralized identity management systems face scalability, privacy, and single-point-of-failure issues when applied to IoT ecosystems. This paper presents a novel blockchain-based framework for decentralized identity management in smart IoT environments. Our proposed framework leverages blockchain technology's immutable ledger, smart contracts, and cryptographic mechanisms to provide secure, scalable, and privacy-preserving identity management for IoT devices. The framework incorporates a multi-layered security architecture that includes device authentication, access control, and identity verification mechanisms. Experimental results demonstrate that our approach achieves 99.7% authentication accuracy with reduced latency compared to traditional centralized systems. The framework also provides enhanced privacy protection through zero-knowledge proofs and selective disclosure mechanisms. This research contributes to the advancement of secure IoT identity management and provides a foundation for future developments in decentralized IoT security
Manufacturing sectors pursuing Industry 5.0 objectives increasingly require automation architectures capable of reasoning across heterogeneous cyber-physical domains while advancing sustainability targets. This paper synthesizes evidence from eighteen references spanning semantic web technologies, cyber-physical systems, digital twins, blockchain-enabled traceability, and multi-agent reinforcement learning to propose a Semantic AI-Orchestrated Cross-Domain Automation Framework for sustainable smart factories. The framework integrates a five-layer architecture, comprising physical sensing, cyber-physical integration, semantic reasoning, cross-domain orchestration, and sustainability decision layers, into a unified reasoning pipeline in which ontology-driven knowledge graphs mediate interoperability among heterogeneous equipment, enterprise systems, and human operators. Comparative synthesis indicates that semantic-based autonomous computing architectures reduce unplanned downtime by as much as 37 percent, while multi-agent reinforcement learning scheduling raises resource utilization to 88 percent relative to 58 percent under conventional rule-based scheduling. Interoperability standards such as OPC-UA demonstrate adoption rates near 78 percent among reviewed implementations, and hybrid semantic-blockchain ledgers achieve transaction throughput exceeding 2,100 transactions per second at latencies below 40 seconds, outperforming public proof-of-work ledgers by more than two orders of magnitude. Digital twin adoption trajectories synthesized from the references rose from approximately 8 percent in 2016 to 66 percent by 2024, correlating with a 24 percent reduction in energy consumption and a 31 percent reduction in material waste across reviewed sustainable manufacturing cases. The findings imply that semantic orchestration, combined with decentralized ledgers and human-centric digital twins, offers a scalable pathway toward resilient, low-carbon, and economically viable smart factory operations, while highlighting persistent challenges in ontology standardization, explainability, and cross-organizational governance.
Qi An, Frank Jiang, Chengzu Dong, Shantanu Pal · 7 authors
The rapid expansion of electric vehicle (EV) infrastructure necessitates advanced solutions for secure and private authentication at EV charging stations. This research introduces a blockchain-based framework enhanced with self-sovereign identity (SSI) features, targeting the improvement of privacy and security in cyber marketplaces for EVs. The inclusion of SSI enables users to maintain full control over their digital identities, a critical advancement for authentication processes at EV charging stations. This system effectively addresses the growing privacy and security challenges within the expanding EV infrastructure. By integrating Zero-knowledge proof with self-sovereign identity, the framework not only ensures robust security but also preserves user privacy by enabling users to prove their identity without exposing sensitive personal information. We propose an efficient and user-friendly solution, showcasing its potential as a pioneering innovation in the field of EV charging infrastructure.
Nik Nor Muhammad Saifudin Nik Mohd Kamal, Safwah Afiqah, Sara Khadeja, Aliya Nasuha · 9 authors
Ethereum and Hyperledger are two popular and well-known block chain platforms which represent two kinds of application differentiation. Ethereum is a decentralized platform that also allows DApps to operate on it; many of the conditions for performing functions on Ethereum’s blockchain do not require permission to be granted, but smart contracts are available. On the other hand, the Hyperledger Fabric, an enterprise grade blockchain solution, provides the permission to access, update, and apply scalability, privatization, and mandatory access control mechanisms. Due to the decentralized nature and the capacity of performing smart contracts using Ethereum Virtual Machine (EVM), it has been used in a number of areas across the world in financial transactions and DApp. Hyperledger fabric, on the other hand, is pursuant to the permissioned network standards and is centred on providing the set of components that suffice the requirement of an enterprise thereby making it easier for the organization to build a blockchain, which is both highly scalable and security conscious. Some of the studies have researched on Ethereum as well as Hyperledger Fabric in a variety of contexts as depicted by the following: From these studies, it explains how blockchain has the potential in increasing volume in various areas while enhancing its characteristics such as, openness, origin and audibility. Analysing the concrete features of the Ethereum and Hyperledger Fabric platforms, it is almost obligatory for the companies interested into the implementation of the blockchain technology to understand the possibilities offered by one system and the drawbacks some complexity or singularity of the other. That is why, the features of each platform are distinctive and could be utilized for the development of business processes in specific spheres when designing problem-solving approaches.
Ammad Aslam, Octavian Postolache, Sancho Oliveira, J. M. Dias Pereira
Sharding is an emerging blockchain technology that is used extensively in several fields such as finance, reputation systems, the IoT, and others because of its ability to secure and increase the number of transactions every second. In sharding-based technology, the blockchain is divided into several sub-chains, also known as shards, that enhance the network throughput. This paper aims to examine the impact of integrating sharding-based blockchain network technology in securing IoT sensors, which is further used for environmental monitoring. In this paper, the idea of integrating sharding-based blockchain technology is proposed, along with its advantages and disadvantages, by conducting a systematic literature review of studies based on sharding-based blockchain technology in recent years. Based on the research findings, sharding-based technology is beneficial in securing IoT systems by improving security, access, and transaction rates. The findings also suggest several issues, such as cross-shard transactions, synchronization issues, and the concentration of stakes. With an increased focus on showcasing the important trade-offs, this paper also offers several recommendations for further research on the implementation of blockchain network technology for securing IoT sensors with applications in environment monitoring. These valuable insights are further effective in facilitating informed decisions while integrating sharding-based technology in developing more secure and efficient decentralized networks for internet data centers (IDCs), and monitoring the environment by picking out key points of the data.
Blockchain-enabled Policy Decision Point (PDP) has been a promising solution to the centralization concern in practical deployment of Attribute-Based Access Control (ABAC). However, existing blockchain systems cannot support PDP adequately since PDP functionalities introduce extra latency to blockchain’s execution process and limits system throughput. This paper proposes an efficient PDP Blockchain (PDPB) by exploiting a minimum-redundancy execution paradigm. Concretely, we design a novel Echo-Based Execution Conclude (EBEC) mechanism to enable minimum redundancy request evaluation while ensure blockchain safety and liveness. Two optimization techniques, Echo Compacting (EC) and Load Balancing (LB), are proposed to reduce the communication and computation overhead of PDPB and further enhance its performance. We implement a prototype of PDPB and evaluate it on Amazon Web Services (AWS) servers. The results show that PDPB achieves more than 35.6% performance improvement over existing methods.
M. Baritha Begum, B. Suganthi, P. Sivagamasundhari, S. A. Arunmozhi · 5 authors
ABSTRACT Mobile ad hoc networks (MANETs) integrated with the Internet of Things (IoT) form a decentralized communication framework crucial for 6G environments. However, ensuring secure and efficient routing in such networks remains a challenge due to their distributed nature and vulnerability to attacks. This paper introduces a heterogeneous local directed acyclic graph blockchain (HLDAG‐BC) combined with recalling enhanced recurrent neural networks (RERNNs) for secure and efficient routing in MANET‐IoT environments. The HLDAG‐BC offers tamper‐proof communication and identity‐based conditional privacy‐preserving authentication (ICPA) is a lightweight and secure node authentication scheme. Network nodes are grouped using the kernel neutrosophic c‐means (KNCM) algorithm. The optimal cluster heads are chosen using the red piranha optimization (RPO) method. RERNN determines the shortest routing path to increase reliability and minimize latency. Furthermore, an HDLNN is used for intrusion detection to achieve robust network security. The HLDAG‐BC‐RERNN approach proposed shows that the packet delivery ratio improves by 31.35%, throughput by 34.56%, latency by 30.29%, and network lifetime by 28.67% compared to the existing approaches, as shown in the comprehensive evaluations. In conclusion, the proposed framework offers a scalable and secure solution for MANET‐IoT networks, making it a viable approach for future 6G applications.
Nowadays, decentralized models connecting various users and entities have gained prominence across the healthcare, finance, and Supply Chain Domains. Decentralized applications represent a transformational approach to data management and transaction execution, emphasizing security, data integrity, and transparency. At the core of these applications lies the blockchain system. This decentralized architecture supports a framework that guarantees data immutability and ensures network-wide transparency through consensus mechanisms. This work aims to explore the application of a blockchain-based system for managing, storing, and signing consent forms within a decentralized framework. By leveraging smart contracts, the system facilitates the creation, modification, deletion, and storage of documents issued by authorized medical entities. Patients can sign these documents, with every alteration and transaction meticulously tracked and recorded, enhancing privacy and data integrity. In addition to these benefits, a private system with role-based access control restricts access to consent forms, as determined by the medical authority that created the documents. The proposed project of this theses aims to leverage these benefits by implementing a Corda application, a blockchain-based solution designed for managing consent forms within the healthcare ecosystem. This solution will enable healthcare providers, patients, and other stakeholders to securely access, share, and manage sensitive medical data with full confidence in its integrity and privacy. By incorporating decentralized technology, the project seeks to create a system where patient consent is stored immutably on the blockchain, ensuring that no unauthorized modifications can be made. Furthermore, the evaluation and testing section of this work reinforces the access security and permission enforcement mechanisms that are proposed and implemented. Rigorous tests and practical examples demonstrate the system's ability to protect patient data and uphold privacy standards, ensuring that only authorized users can interact with sensitive information.
With the continuous advancement of the Uncrewed Aerial Vehicle (UAV) communication industry, the efficient allocation of scarce spectrum resources to UAVs has become a pressing issue. Given the unique nature of UAVs and the broadcast nature of wireless channels, there are significant instances of unregulated flight operations and malicious attacks, making it essential to ensure the security and fairness of spectrum allocation. The previous work on spectrum sharing schemes seldom considers UAV communication scenarios and fails to consider the transaction environment. This paper employs combinatorial auctions and Stackelberg games to study spectrum trading between multiple base stations (BSs) and UAVs to address these issues. A dynamic, demand-driven spectrum trading model is proposed that accounts for UAVs' flexibility and evolving spectrum needs, maximizing utility for both UAVs and BSs. Subsequently, a blockchain-based spectrum sharing framework is designed, in which the blockchain is made public to trading participants to uphold decentralization. It reflects transactional fairness and reliability through mutual evaluations between the blockchain management platform and trading participants. To simulate a realistic trading environment, we consider specific attack scenarios to assess the credibility guarantee of spectrum trading under blockchain. The simulation results validate the effectiveness of the blockchain-based spectrum trading scheme, enhancing spectrum utilization, ensuring the utility of all entities involved, and maintaining the reliability of the trading process.
This paper explores the rethinking of blockchain architecture for the Internet of Things (IoT) to improve data security, integrity, and processing efficiency. An API gateway collects, prepares, and sends data to blockchain nodes for verification when integrating IoT devices with a blockchain network. Accuracy is ensured by updating the distributed ledger with verified data. Within the blockchain, smart contracts automate actions in response to IoT data situations, carrying out tasks automatically and recording results. Large or supplemental data is stored off-chain to preserve efficiency and scalability, while basic transactional data is kept in the distributed ledger. Direct connection between blockchain nodes via a peer-to-peer (P2P) network promotes fault tolerance, consensus, and data consistency. This architecture utilizes the secure and immutable properties of blockchain technology to address common IoT challenges, offering a robust solution for contemporary IoT applications.
Tamai Ramírez-Gordillo, Antonio Maciá-Lillo, Francisco A. Pujol, Nahuel García-D’Urso · 6 authors
The exponential growth of the Internet of Things (IoT) necessitates robust, scalable, and secure identity management solutions to handle the vast number of interconnected devices. Traditional centralized identity systems are increasingly inadequate due to their vulnerabilities, such as single points of failure, scalability issues, and limited user control over data. This study explores a decentralized identity management model leveraging the IOTA Tangle, a Directed Acyclic Graph (DAG)-based distributed ledger technology, to address these challenges. By integrating Decentralized Identifiers (DIDs), Verifiable Credentials (VCs), and IOTA-specific technologies like IOTA Identity, IOTA Streams, and IOTA Stronghold, we propose a proof-of-concept framework that enhances security, scalability, and privacy in IoT ecosystems. Our implementation on resource-constrained IoT devices demonstrates the feasibility of this approach, highlighting significant improvements in transaction efficiency, real-time data exchange, and cryptographic key management. Furthermore, this research aligns with Web 3.0 principles, emphasizing decentralization, user autonomy, and data sovereignty. The findings suggest that IOTA-based solutions can effectively advance secure and user-centric identity management in IoT, paving the way for broader applications in various domains, including smart cities and healthcare.
Shoubai Nie, Jingjing Ren, Rui Wu, Pengchong Han · 6 authors
Within the framework of 6G networks, the rapid proliferation of Internet of Things (IoT) devices, coupled with their decentralized and heterogeneous characteristics, presents substantial security challenges. Conventional centralized systems face significant challenges in effectively managing the diverse range of IoT devices, and they are inadequate in addressing the requirements for reduced latency and the efficient processing and analysis of large-scale data. To tackle these challenges, this paper introduces a zero-trust access control framework that integrates blockchain technology with inner-product encryption. By using smart contracts for automated access control, a reputation-based trust model for decentralized identity management, and inner-product encryption for fine-grained access control, the framework ensures data security and efficiency. Firstly, smart contracts are employed to automate access control, and software-defined boundaries are defined for different application domains. Secondly, through a trust model based on a consensus algorithm of node reputation values and a registration-based inner-product encryption algorithm supporting fine-grained access control, zero-trust self-sovereign enhanced identity management in the 6G environment of the Internet of Things is achieved. Furthermore, the use of multiple auxiliary chains for storing data across different application domains not only mitigates the risks associated with data expansion but also achieves micro-segmentation, thereby enhancing the efficiency of access control. Finally, empirical evidence demonstrates that, compared with the traditional methods, this paper's scheme improves the encryption efficiency by 14%, reduces the data access latency by 18%, and significantly improves the throughput. This mechanism ensures data security while maintaining system efficiency in environments with large-scale data interactions.
Ahmed Alagha, Maha Kadadha, Rabeb Mizouni, Shakti Singh · 6 authors
This paper addresses the challenges of selecting relay nodes and coordinating among them in UAV-assisted Internet-of-Vehicles (IoV). Recently, UAVs have gained popularity as relay nodes to complement vehicles in IoV networks due to their ability to extend coverage through unbounded movement and superior communication capabilities. The selection of UAV relay nodes in IoV employs mechanisms executed either at centralized servers or decentralized nodes, which have two main limitations: 1) the traceability of the selection mechanism execution and 2) the coordination among the selected UAVs, which is currently offered in a centralized manner and is not coupled with the relay selection. Existing UAV coordination methods often rely on optimization methods, which are not adaptable to different environment complexities, or on centralized deep reinforcement learning, which lacks scalability in multi-UAV settings. Overall, there is a need for a comprehensive framework where relay selection and coordination processes are coupled and executed in a transparent and trusted manner. This work proposes a framework empowered by reinforcement learning and Blockchain for UAV-assisted IoV networks. It consists of three main components: a two-sided UAV relay selection mechanism for UAV-assisted IoV, a decentralized Multi-Agent Deep Reinforcement Learning (MDRL) model for efficient and autonomous UAV coordination, and finally, a Blockchain implementation for transparency and traceability in the interactions between vehicles and UAVs. The relay selection considers the two-sided preferences of vehicles and UAVs based on the Quality-of-UAV (QoU) and the Quality-of-Vehicle (QoV). Upon selection of relay UAVs, the coordination between the selected UAVs is enabled through an MDRL model trained to control their mobility and maintain the network coverage and connectivity using Proximal Policy Optimization (PPO). MDRL offers decentralized control and intelligent decision-making for the UAVs to maintain coverage and connectivity over the assigned vehicles. The evaluation results demonstrate that the proposed selection mechanism improves the stability of the selected relays, while MDRL maximizes the coverage and connectivity achieved by the UAVs. Both methods show superior performance compared to several benchmarks.