Blockchain Papers

Vikram Puri, Vijender Kumar Solanki, Gloria Jeanette Rincón-Aponte

No abstract is available for this record.

Zeeshan Ali Siddiqui, Mohd Haroon

No abstract is available for this record.

Qing Zhang, Jingyi Du, Peiyu Zheng, Lu Zhang · 8 authors

As one of the most concerned Internet technologies in recent years, blockchain technology is in the process of accelerating its evolution and maturity. The blockchain is gradually integrated with other Internet technologies and applied in many industries, providing decentralized solutions for various industries, realizing innovative storage models, and building a new trust system. As one of the largest international standardization organizations, the Telecommunication Standardization Sector of the International Telecommunication Union (ITU-T) has published standards with great influence in the world, and there are many standards published and under development in the field of blockchain technology, and the types of standards are abundant. This paper first introduces the organizational structure and workflow of ITU. Then it introduces study and achievements on blockchain, including the focus group established by ITU-T and the standards published and under development by multiple study groups. It makes a statistical analysis of the standards, and expects that the blockchain standards will be more diverse in the future to meet the needs of industrial development.

Zhuotao Lian, Qingkui Zeng, Weizheng Wang, Thippa Reddy Gadekallu · 5 authors

The Internet of Medical Things (IoMT) has a bright future with the development of smart mobile devices. Information technology is also leading changes in the healthcare industry. IoMT devices can detect patient signs and provide treatment guidance and even instant diagnoses through technologies, such as artificial intelligence (AI) and wireless communication. However, conventional centralized machine learning approaches are often difficult to apply within IoMT devices because of the difficulty of large-scale collection of patient data and the potential risk of privacy breaches. Therefore, we propose a blockchain-based two-stage federated learning approach that allows IoMT devices to train a global model collaboratively without gathering the data to a central server. Specifically, to address the problem of poor training performance on non-independent identically distributed (non-IID) data, we design a blockchain-based data-sharing scheme that can significantly improve the model’s accuracy without threatening user privacy. We also design a client selection mechanism to further improve the system’s efficiency. Finally, we validate the feasibility and effectiveness of our system through simulation experiments on three popular datasets (i.e., MNIST, Fashion-MNIST, and CIFAR-10).

Tharindu Ranathunga, Alan McGibney, Susan Rea, Sourabh Bharti

Traditional federated learning (FL) adopts a client-server architecture where FL clients (e.g., IoT edge devices) train a common global model with the help of a centralized orchestrator (cloud server). However, current approaches are moving away from centralized orchestration toward a decentralized one in order to fully adapt FL for a cross-silo configuration with multiple organizations acting as clients. State-of-the-art decentralized FL mechanisms make at least one of the following assumptions: 1) clients are trusted organizations and cannot inject low-quality model updates for aggregation and 2) client local models can be shared with other clients or a third party for verification of low-quality updates. This article proposes a Blockchain-based decentralized framework for scenarios where participatory organizations are believed to be fully capable of injecting low-quality model updates as they are not willing to expose their local models to any other entity for verification purpose. The proposed decentralized FL framework adopts a novel hierarchical network of aggregators with the ability to punish/reward organizations in proportion to their local model quality updates. The framework is flexible and unlike state-of-the-art solutions, prevents a single entity from possessing the aggregated model in any FL round of training. The proposed framework is tested with respect to off-chain and on-chain performance in two Industry 4.0 use cases: 1) predictive maintenance and 2) product visual inspection. A comparative evaluation against the state-of-the-art reveals the proposed framework’s utility in terms of minimizing model convergence time and latency while maximizing accuracy and throughput.

Ismaeel Al Ridhawi, Moayad Aloqaily, Ali Abbas, Fakhri Karray

The shift towards Industry 4.0 has seen significant steps forward with the advancements in processing, communication, and storage capabilities of Internet of Things (IoT) devices. Cyber-physical systems (CPS) have become more intelligent and withhold advanced processing, storage, and communication capabilities. Rejuvenated network and service management architectures must incorporate the capabilities of intelligent CPS. With that said, this article introduces a cooperative blockchain (BC)-assisted resource and capability sharing approach to fulfill CPS tasks. The solution uses Federated Learning (FL)-enabled Intelligent IoT (IIoT) devices to support Next-Generation Networks (NGNs). A clustering multi-stage blockchain and FL algorithm is used to create local and global models for CPS tasks. Local models are created for each cluster during the first stage. At the second stage, Federated Averaging is used by fog devices to create fog models. A global deep model is then created on the cloud using Federated Aggregation. Blockchain is used to record and validate the added models and ensure that records are not altered under cyber-attacks. Simulation results have shown that the proposed solution outperforms conventional FL and blockchain approaches in terms of accuracy and delay tolerance.

T. Manikandan, Shajahan Basheer, Shitharth Selvarajan, Sara A. Althubiti · 7 authors

There can be many inherent issues in the process of managing cloud infrastructure and the platform of the cloud. The platform of the cloud manages cloud software and legality issues in making contracts. The platform also handles the process of managing cloud software services and legal contract-based segmentation. In this paper, we tackle these issues directly with some feasible solutions. For these constraints, the Averaged One-Dependence Estimators (AODE) classifier and the SELECT Applicable Only to Parallel Server (SELECT-APSL ASA) method are proposed to separate the data related to the place. ASA is made up of the AODE and SELECT Applicable Only to Parallel Server. The AODE classifier is used to separate the data from smart city data based on the hybrid data obfuscation technique. The data from the hybrid data obfuscation technique manages 50% of the raw data, and 50% of hospital data is masked using the proposed transmission. The analysis of energy consumption before the cryptosystem shows the total packet delivered by about 71.66% compared with existing algorithms. The analysis of energy consumption after cryptosystem assumption shows 47.34% consumption, compared to existing state-of-the-art algorithms. The average energy consumption before data obfuscation decreased by 2.47%, and the average energy consumption after data obfuscation was reduced by 9.90%. The analysis of the makespan time before data obfuscation decreased by 33.71%. Compared to existing state-of-the-art algorithms, the study of makespan time after data obfuscation decreased by 1.3%. These impressive results show the strength of our methodology.

Zigui Jiang, Kai Chen, Hailin Wen, Zibin Zheng

Smart contract has been the core of blockchain systems and other blockchain-based systems since Blockchain 2.0. Various operations on blockchain are performed through the invocation and execution of smart contracts. This leads to extensive combinations between blockchain, smart contract, Internet of Things (IoT) and Cyber-Physical System (CPS) applications, and then many blockchain-based IoT or CPS applications emerge to provide multiple benefits to the economy and society. In this case, obtaining a better understanding of smart contracts will contribute to the easier operation, higher efficiency and stronger security of those blockchain-based systems and applications. Many existing studies on smart contract analysis are based on similarity calculation and smart contract classification. However, smart contract is a piece of code with special characteristics and most of smart contracts are stored without any category labels, which leads to difficulties of smart contract classification. As the back end of a blockchain-based Decentralized Application (DApp) is one or several smart contracts, DApps with labeled categories and open source codes are applied to achieve a supervised smart contract classification. A three-phase approach is proposed to categorize DApps based on various data features. In this approach, 5,659 DApps with smart contract source codes and pre-tagged categories are first obtained based on massive collected DApps and smart contracts from Ethereum, State of the DApps and DappRadar. Then feature extraction and construction methods are designed to form multi-feature vectors that could present the major characteristics of DApps. Finally, a fused classification model consisting of KNN, XGBoost and random forests is applied to the multi-feature vectors of all DApps for performing DApp classification. The experimental results show that the method is effective. In addition, some positive correlations between feature variables and categories, as well as several user behavior patterns of DApp calls, are found in this paper.

Kawther A. Al‐Dhlan, Hamad A. Alreshidi, Shahbaz Pervez, Zahida Paraveen · 8 authors

The adoption of blockchain technology can provide data asset management’s high security, privacy, and traceability. After a comprehensive investigation of the present blockchain-based data asset management mechanism, it was determined that it is only relevant to a portion of the blockchain system design. To address this issue, a new model of data asset management based on blockchain technology is being developed, which incorporates applications at all levels of the blockchain system. This model implements a network layer node authority control mechanism, a consensus layer consensus mechanism with customizable attributes, improved data query efficiency at the data layer by optimizing the structure and building indexes, intelligent data management, and smart contract layer management. Furthermore, at the transaction layer, sharing information encryption using customizable encryption algorithms is introduced. The experimental results reveal that, when compared to the traditional paradigm, the new blockchain-based data asset management strategy enhances the efficiency of on-chain data queries by 2.33 times.

Sandi Rahmadika, Philip Virgil Astillo, Gaurav Choudhary, Daniel Gerbi Duguma · 6 authors

The Internet of Medical Things (IoMT) has risen to prominence as a possible backbone in the health sector, with the ability to improve quality of life by broadening user experience while enabling crucial solutions such as near real-time remote diagnostics. However, privacy and security problems remain largely unresolved in the safety area. Various rule-based methods have been considered to recognize aberrant behaviors in IoMT and have demonstrated high accuracy of misbehavior detection appropriate for lightweight IoT devices. However, most of these solutions have privacy concerns, especially when giving context during misbehavior analysis. Moreover, falsified or modified context generates a high percentage of false positives and sometimes causes a by-pass in misbehavior detection. Relying on the recent powerful consolidation of blockchain and federated learning (FL), we propose an efficient privacy-preserving framework for secure misbehavior detection in lightweight IoMT devices, particularly in the artificial pancreas system (APS). The proposed approach employs privacy-preserving bidirectional long-short term memory (BiLSTM) and augments the security through integrating blockchain technology based on Ethereum smart contract environment. The effectiveness of the proposed model is bench-marked empirically in terms of sustainable privacy preservation, commensurate incentive scheme with an untraceability feature, exhaustiveness, and the compact results of a variant neural network approach. As a result, the proposed model has a 99.93% recall rate, showing that it can detect virtually all possible malicious events in the targeted use case. Furthermore, given an initial ether value of 100, the solution's average gas consumption and Ether spent are 84,456.5 and 0.03157625, respectively.

Baofeng Ji, Mingkun Zhang, Ling Xing, Xiaoli Li · 7 authors

The huge increase in the communication network rate has made the application fields and scenarios for vehicular ad hoc networks more abundant and diversified and proposed more requirements for the efficiency and quality of data transmission. To improve the limited communication distance and poor communication quality of the Internet of Vehicles (IoV), an optimal intelligent routing algorithm is proposed in this paper. Combined multi-weight decision algorithm with the greedy perimeter stateless routing protocol, designed and evaluated standardized function for link stability. Linear additive weighting is used to optimize link stability and distance to improve the packet delivery rate of the IoV. The blockchain system is used as the storage structure for relay data, and the smart contract incentive algorithm based on machine learning is used to encourage relay vehicles to provide more communication bandwidth for data packet transmission. The proposed scheme is simulated and analyzed under different scenarios and different parameters. The experimental results demonstrate that the proposed scheme can effectively reduce the packet loss rate and improve system performance.

Hongliang Tian, Yuzhi Jian, Xiaonan Ge

No abstract is available for this record.

Abdulrahman Alqarafi, Fadwa Alrowais, Saud S. Alotaibi, Nadhem Nemri · 9 authors

Currently, the amount of Internet of Things (IoT) applications is enhanced for processing, analyzing, and managing the created big data from the smart city. Certain other applications of smart cities were location-based services, transportation management, and urban design, amongst others. There are several challenges under these applications containing privacy, data security, mining, and visualization. The blockchain-assisted IoT application (BIoT) is offering new urban computing to secure smart cities. The blockchain is a secure and transparent data-sharing decentralized platform, so BIoT is suggested as the optimum solution to the aforementioned challenges. In this view, this study develops an Optimal Machine Learning-based Intrusion Detection System for Privacy Preserving BIoT with Smart Cities Environment, called OMLIDS-PBIoT technique. The presented OMLIDS-PBIoT technique exploits BC and ML techniques to accomplish security in the smart city environment. For attaining this, the presented OMLIDS-PBIoT technique employs data pre-processing in the initial stage to transform the data into a compatible format. Moreover, a golden eagle optimization (GEO)-based feature selection (FS) model is designed to derive useful feature subsets. In addition, a heap-based optimizer (HBO) with random vector functional link network (RVFL) model was utilized for intrusion classification. Additionally, blockchain technology is exploited for secure data transmission in the IoT-enabled smart city environment. The performance validation of the OMLIDS-PBIoT technique is carried out using benchmark datasets, and the outcomes are inspected under numerous factors. The experimental results demonstrate the superiority of the OMLIDS-PBIoT technique over recent approaches.

Mehmet Ozgen Ozdogan, Levent Çarkacıoğlu, Berk Canberk

With the rapid development of intelligent devices in wireless communication, the fifth generation (5G) mobile networks have limited high data rates, low latency, high avail-ability demands. The sixth-generation (6G) mobile network can use Digital-twin (DT) techniques to meet these demands. DT is the virtual representation of physical aspects such as 6G edge nodes. DT optimize the 6G edge nodes parameters using artificial intelligence (AI) and especially machine learning (ML) algorithms. However, AI and ML bring along privacy and security concerns. Therefore, user data must be protected from unauthorized persons during the 6G edge network recovery and expansion phases. In this paper, we proposed a new reliable Digital Twin-based 6G edge network recovery framework using Blockchain technology. We applied the Transfer Learning (TL) technique to improve our proposed framework’s performance. We ensured data privacy and security using TL and Blockchain.

Ihab L. Hussein Alsammak, Mohammed F. Alomari, Intedhar Shakir Nasir, Wasan H. Itwee

Recently, with the emergence and growth of the IoT as a promising vehicle for sustainable development, the concept of ‘smart cities’ has advanced significantly. However, many challenges inhibit the development of using IoT applications in smart cities, such as issues of privacy, scalability, trust, security, and centralisation. On a daily basis in smart cities, the IoT generates a large amount of data (big data) which could potentially be used for questionable or suspect purposes by attackers. The weight of the security issues surrounding big data must be acknowledged as the associated technology is continuously developing. To solve this issue, a strategy that secures important and potentially sensitive user information on a distributed blockchain and transmits non-sensitive information to the primary system by controlling the size of the blockchain is proposed. This solution cannot be achieved in traditional blockchain because it requires too many resources. The model is composed of three proposed algorithms: the first aims to allocate data to each user; the second performs the process of searching for data, and the third confirms the communication process. Experiments have proved that this proposed protocol for blockchain has excellent byzantine fault tolerance. The final experimental results of the proposed model established that the algorithms effectively meet the performance requirements.

Xiuwen Tang, Jiazhen Gan, Zigui Jiang

Smart contracts can be considered as a service in the blockchain system and have been applied in many fields, covering financial products, online games, real estate, transportation and logistics. However, smart contract technology is still in its infancy. Development task is facing many difficulties and challenges, thus providing a set of new or improved development aids for the smart contract ecosystem is an urgent problem that needs to be solved. This paper proposes a smart contract code recommendation method based on graph neural network, which aims to facilitate the development of smart contracts and help developers realize smart contracts faster and more securely. Experimental results show that this method is better than the existing model of smart contract code recommendation in terms of accuracy.

P.G. Giardina G. Bernini

This document presents the final design of the 5GZORRO high-level architecture, which targets the achievement and implementation of the innovative 5G networks and services vision described above. More specifically, this deliverable is intended as a self-contained document, which merges the original content of deliverables D2.2 and D2.3 (that present the initial and the updated 5GZORRO high-level architecture respectively) and further improves them to align the 5GZORRO architecture functionalities with the feedback from the platform implementation undergoing in WP3 and WP4. With this document, the goal is to have a single source of information for the 5GZORRO high-level architecture, which includes the whole set of services offered, functionalities supported, and operational workflows implemented.<br> In practice, in alignment with the original approach proposed and described in D2.2 and D2.3, the architecture follows a principle of service-based architecture, similar to the 5G Service-based architecture defined in 3GPP and in the ETSI Zero touch network and Service Management. Integrating SDN/NFV and Cloud native orchestration technologies with a Permissioned Distributed Ledger infrastructure, the 5GZORRO architecture offers services for:<br> • cross-domain network slicing,<br> • resource and service offering via marketplaces,<br> • discovery, intelligent selection and trading of resources and Services via Smart Contracts<br> • zero-touch network slice and service lifecycle management<br> • cross-stakeholder e-license management<br> • SLA monitoring &amp; breach prediction<br> • security and trust across multiple domains.<br> The realization of these services is made possible through the interaction of various functions for slice orchestration, network intelligence and analytics, security and trust, management of virtualized resources, all executed for multi-domain and single domain scopes. Moreover, 5GZORRO leverages many state-of-the-art technologies and standards for virtualization, NFV, Cloud Native platforms and services, zero touch, SDN, distributed ledgers, data lakes, which have been extensively reviewed to summarise the specific positioning of the 5GZORRO innovative proposition.

Bo Zhao, Chenhan Shangguan, Xiaoyan PENG, Yang AN · 6 authors

In order to solve the problems of low detection accuracy and high false positive rate of traditional smart contract vulnerability detection methods and less consideration of bytecode level smart contract features in neural networks, a smart contract bytecode vulnerability detection method based on semantic perception graph neural network was proposed. First, in order to generate the control flow graph, the basic blocks divided by the smart contract bytecode were used as the nodes, and the call relationship between the basic blocks was extracted from the bytecode as the edges. Then, control flow graph is transmitted into the graph convolutional network for training to obtain the feature representation of the graph nodes; Afterwards, the contract bytecode instruction sequence is segmented, transformed into a word vector, embedded into a low-dimensional space and transmitted to a long short-term memory network for training. Then, the vector representation of bytecode semantic information was obtained. Finally, the generated node features and semantic features were spliced and transmitted to the full connection layer for dimensionality reduction. Combined with semantic information and node features, the vulnerability detection was carried out for smart contracts. The real smart contracts in public dataset were used for training and testing, and verified in two types of vulnerability classification datasets through traditional methods and artificial tags. The method proposed in this paper was compared with three traditional smart contract vulnerability detection tools and one smart contract vulnerability detection method based on neural network. The experimental results showed that the proposed network greatly improves the performance of network in terms of various indicators, and detects the contracts with vulnerabilities which are not detected by the other four methods. It shows that adding the bytecode semantic information to graph neural network can effectively improve the detection accuracy and reduce the false alarm rate.

Imran Ahmed, Yulan Zhang, Gwanggil Jeon, Wenmin Lin · 6 authors

Advancements in digital technologies, such as the Internet of Things (IoT), fog/edge/cloud computing, and cyber-physical systems have revolutionized a broad spectrum of smart city applications. The significant contributions and rapid developments of advanced artificial intelligence-based technologies and approaches, like, machine learning and deep learning, which are applied for extracting accurate information from extensive data, perform a potential role in IoT applications. Moreover, blockchain technology's fast adoption also contributes a significant role in the development of the new digital smart city ecosystem. Thus, artificial intelligence and blockchain technology convergence revolutionize smart city infrastructures to establish sustainable ecosystems for IoT applications. Nevertheless, these advancements and technological improvements also provide both opportunities and challenges for developing sustainable IoT applications. This paper aims to examine the convergence of blockchain technology and artificial intelligence, a unique driver towards technological transformation in intelligent and sustainable IoT applications. We mainly discussed the advantages of blockchain technology that might promote the advancement and development of sustainable IoT applications. On the basis of the discussion, we introduced a smart and sustainable conceptual framework that leverages cloud computing, IoT devices, and artificial intelligence to process and obtain necessary information. The system provides digital analytics and saves results in decentralized cloud repositories through blockchain technology to promote various applications. Moreover, the layer-based architecture allows a sustainable incentive structure, which can possibly assist secure and protected smart city applications. We reviewed the enhanced solutions, summing up the key points that can be applied for generating various artificial intelligence and blockchain-based systems. Also, we discussed the issues that still remain open and our future research goals; that can introduce new ideas and future guidelines for sustainable IoT applications.

Tripti Sharma, Sanjeev Kumar Prasad, Vedangi Sharma

Nowadays, video calling is very much on demand, and it is working well in 4G and 5G networks. It is a time for 3D calling, virtual reality live streaming and holographic communication; Accessing this type of data requires ultrahigh data rates and traffic volumes, so there is a need to speed up the network and increase bandwidth. On the other hand, a system has to maintain reliability, security, availability and flexibility in a wireless network. The network should be extended to the needs of human life such as entertainment, healthcare, smart cities, and transportation expected to enhance service quality with a high-end user experience. To establish this network, the telecommunications infrastructure must upgrade its unmatched service level requirements. The two major disruptive emerging components in this modern Internet-enabled era of technology are both the blockchain and the Internet of Things (IoT). In research and industry, IoT has experienced exponential growth, although it suffers from several limitations, such as poor interoperability, decentralization, privacy, and security vulnerabilities. 6G applications can be based on telecommunications networks and IoT, therefore, the network must ensure strong connectivity between nodes and also ensure the privacy and security of user data. Blockchain is the appropriate solution for these issues. Blockchain is a distributed ledger technology and it enables many industries to exchange data over the Internet between trusted parties without using a central server. The blockchain facilitates verifiable, transparent and secure digital asset transactions with proof of right and ownership. There is a need to identify the role of blockchain in 6G networks. This paper explores the challenges and opportunities related to blockchain for 6G networks, future application possibilities and upcoming research directions.

Zhenjun Xie, Hua Kong, Bin Wang

In this paper, we consider the Vennia algorithm to conduct in-depth research and analysis on the traceability of dual-chain blockchain agricultural products' E-commerce information. This paper adds a collaborative verification module to the traceability system and carries out a detailed design of information storage, traceability consensus algorithm, and smart contract for agricultural products according to the characteristics of the agricultural products supply chain, among which the collaborative verification module adopts dynamic data storage technology; the ConsiderVinia consensus algorithm is improved by introducing the way of integral penalty mechanism to ensure the block data validity. After a comparative study of the features and differences of the three major blockchain technology platforms, this paper selects the super ledger to implement the agricultural traceability system based on blockchain technology, introduces the partitioning and credit mechanism into the ConsiderVinia algorithm, and elaborates the improvement process of the algorithm. The improved algorithm reduces the malicious behavior of nodes and maintains the system security through a credit mechanism while maintaining the consistency of blockchain. In the event of a transaction dispute, the third-party platform will determine the party at fault based on the transaction records and other evidence and make corresponding punishments and compensations. The experiment proves that the algorithm proposed in this paper can reduce the amount of network data transmission in the process of node consensus, which is better than the ConsiderVinia algorithm in terms of both throughput and latency, improves the consensus efficiency, and alleviates the communication bottleneck caused by the increase of users in blockchain applications, and the solution of applying the blockchain technology to the agricultural products traceability system is practical and feasible. The blockchain-based agricultural products information traceability system solves the problems of information asymmetry, difficult sharing, easy tampering, and storage centralization in the traditional IoT-based agricultural products traceability system and truly realizes the credible and reliable traceability of the whole chain of agricultural products information. The research content and results of this paper have certain theoretical and practical values.

Omaji Samuel, Akogwu Blessing Omojo, Abdulkarim Musa Onuja, Yunisa Sunday · 10 authors

Internet of medical things (IoMT) has made it possible to collect applications and medical devices to improve healthcare information technology. Since the advent of the pandemic of coronavirus (COVID-19) in 2019, public health information has become more sensitive than ever. Moreover, different news items incorporated have resulted in differing public perceptions of COVID-19, especially on the social media platform and infrastructure. In addition, the unprecedented virality and changing nature of COVID-19 makes call centres to be likely overstressed, which is due to a lack of authentic and unregulated public media information. Furthermore, the lack of data privacy has restricted the sharing of COVID-19 information among health institutions. To resolve the above-mentioned limitations, this paper is proposing a privacy infrastructure based on federated learning and blockchain. The proposed infrastructure has the potentials to enhance the trust and authenticity of public media to disseminate COVID-19 information. Also, the proposed infrastructure can effectively provide a shared model while preserving the privacy of data owners. Furthermore, information security and privacy analyses show that the proposed infrastructure is robust against information security-related attacks.

Haitao Liu, Zhipeng Lv, Zhenhao Song, Shan Zhou · 6 authors

With the continuous development of urban intelligence, as traffic, power grids, and electric vehicles are new ideas to solve energy shortages and air control problems, they have received widespread attention from the society and strong support from the government. The charging pile is a key hub for data exchange and has typical characteristics of IoT terminals. However, the guidance of the grid connection of electric vehicles is not standardized, and the security and stability of the power grid will inevitably be affected. The blockchain has the characteristics that data is difficult to tamper with and decentralized. Based on these two characteristics, the information recorded by the blockchain is more authentic and reliable. This paper is aimed at realizing the global unified identification and management of large terminal equipment based on ubiquitous power Internet of Things equipment with the help of blockchain technology and at providing safe, efficient, and stable online management services for a large number of devices in the ubiquitous power Internet of Things. In this paper, we analyze the application possibility of blockchain technology in the current electricity market and apply blockchain technology to the electricity market to solve the drawbacks of the electricity market, as well as adding blockchain analytics to the renewable energy electricity market. The experimental data analysis shows that with the increase of the length of the blockchain, the blocking time of the new area increases correspondingly, but the overall performance declines slightly, so this scheme can meet the practical needs of a large number of concurrent access terminals in the ubiquitous power Internet of Things. It can be seen that the successful application of blockchain technology based on the power Internet of Things in electric vehicle charging piles has greatly improved work efficiency.

Tingting Yang, Zhengqi Cui, Asma Hassan Alshehri, Miao Wang · 6 authors

In recent years, with the continuous development of internet of things (IoT) technology, many fields have benefited a lot, including the maritime transportation system (MTS). But there are also corresponding risks, such as security and privacy, interference attacks, ransomware attacks, and so on. How to ensure the reliability and efficiency of information transmission is very important for maritime transportation system. In order to solve this problem, we propose an IoT-enabled maritime transport communication system, which is a distributed system composed of base stations and offshore buoys, and uses the unique structure of the blockchain to solve the problems of security and reliability in the network. There are two main advantages: First, the decentralized network is reliable and can handle node failures. Second, the use of blockchain technology can integrate computing resources into the entire network to support different tasks, while taking into account information security and transaction security. On this basis, with the help of edge computing technology, we have also improved the energy efficiency and performance of IoT devices in the system.