【Author】 Li, Ting Liu, Wei Liu, Anfeng Dong, Mianxiong Ota, Kaoru Xiong, Neal N. Li, Qiang

【Source】IEEE INTERNET OF THINGS JOURNAL CCF-C

【影响因子】10.238

【主题类别】

区块链治理-技术治理-信任

【Abstract】Recent developments in collection, computation and communication have expanded the way of data reporting in intelligent Internet of Things (IoT). However, diversity and complexity of data sources also impose new trust challenge in data collection process since untrust reporters tend to report false or even malicious data, which highlights the need to develop a novel methodology to solve such challenge. Thus, based on this domain, inspired by deterrence theory, this article proposes a blockchain-based trust system with assistant of drones to deter malicious data reporting in intelligent IoT. Specifically, to deter malicious data reporting, based on the blockchain technology, the data sensed by fully trusted drones is public published on blockchain showing participants the data standards, named as malicious deterrence scheme. This scheme provides a barrier for malicious reporters to arbitrarily publish false data to blockchain, since the false data can be easily detected while they cannot deny. Second, to further reduce malicious data reporting, a strict penalty mechanism is proposed to punish malicious reporters who have reported false data to blockchain to reduce the malicious data reporting in the following task through punishment. Third, note that the sensing of data standard generates additional costs, therefore, a drone flight route scheme based on a simper deep reinforcement learning with multihead attention mechanism (MA-DRL) is designed to reduce the flight distance for drones. Finally, extensive experiments demonstrate efficiency of our proposed system in terms of reducing malicious data reporting in advance as well as reducing drone flight distance.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchain; Drones; Internet of Things; Crowdsourcing; Distributed databases; Data models; Task analysis; Blockchain; deep reinforcement learning (DRL); drones; intelligent Internet of Things (IoT); malicious data; trust

【发表时间】2022

【收录时间】2022-11-20

【文献类型】 实证数据

【DOI】 10.1109/JIOT.2021.3085004

【Author】 Li, Meng Pei, Pan Yu, F. Richard Si, Pengbo Li, Yu Sun, Enchang Zhang, Yanhua

【Source】IEEE INTERNET OF THINGS JOURNAL CCF-C

【影响因子】10.238

【主题类别】

区块链技术-协同技术-物联网

【Abstract】Driven by numerous emerging mobile devices and various Quality-of-Service (QoS) requirements, mobile-edge computing (MEC) has been recognized as a prospective paradigm to promote the computation capability of mobile devices, as well as reduce energy overhead and service latency of applications for the Internet of Things (IoT). However, there are still some open issues in the existing research works: 1) limited network and computing resource; 2) simple or nonintelligent resource management; and 3) ignored security and reliability. In order to cope with these issues, in this article, 6G and blockchain technology are considered to improve network performance and ensure the authenticity of data sharing for the MEC-enabled IoT. Meanwhile, a novel intelligent optimization method named as collective reinforcement learning (CRL) is proposed and introduced, to realize intelligent resource allocation, meet distributed training results sharing, and avoid excessive consumption of system resources. Based on the designed network model, a cloud-edge collaborative resource allocation framework is formulated. By joint optimizing the offloading decision, block interval, and transmission power, it aims to minimize the consumption overheads of system energy and latency. Then, the formulated problem is designed as a Markov decision process, and the optimal strategy can be obtained by the CRL. Some evaluation results reveal that the system performance based on the proposed scheme outperforms other existing schemes obviously.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Internet of Things; Blockchains; 6G mobile communication; Resource management; Optimization; Computational modeling; Servers; Blockchain; collective reinforcement learning (CRL); Internet of Things (IoT); mobile-edge computing (MEC); sixth generation (6G)

【发表时间】2022

【收录时间】2022-11-20

【文献类型】 实证数据

【DOI】 10.1109/JIOT.2022.3185289

【Author】 Baucas, Marc Jayson Spachos, Petros Plataniotis, Konstantinos N.

【Source】IEEE INTERNET OF THINGS JOURNAL CCF-C

【影响因子】10.238

【主题类别】

区块链技术-协同技术-物联网

【Abstract】The number of embedded devices that connect to a wireless network has been growing for the past decade. This interaction creates a network of Internet-of-Things (IoT) devices where data travel continuously. With the increase of devices and the need for the network to extend via fog computing, we have fog-based IoT networks. However, with more endpoints introduced to it, the network becomes open to malicious attackers. This work attempts to protect fog-based IoT networks by creating a platform that secures the endpoints through public-key encryption. The servers are allowed to mask the data packets shared within the network. To be able to track all of the encryption processes, we incorporated the use of permissioned blockchains. This technology completes the security layer by providing an immutable and automated data structure to function as a hyper ledger for the network. Each data transaction incorporates a handshake mechanism with the use of a public-key pair. This design guarantees that only devices that have proper access through the keys can use the network. Hence, management is made convenient and secure. The implementation of this platform is through a wireless server-client architecture to simulate the data transactions between devices. The conducted qualitative tests provide an in-depth feasibility investigation on the network's levels of security. The results show the validity of the design as a means of fortifying the network against endpoint attacks.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchains; Security; Servers; Internet of Things; Cryptography; Public key; Edge computing; Fog computing; Fog-IoT network; Internet of Things (IoT); permissioned blockchain; privacy; security

【发表时间】2022

【收录时间】2022-11-20

【文献类型】 实证数据

【DOI】 10.1109/JIOT.2021.3104740

【Author】 Adil, Muhammad Jan, Mian Ahmad Mastorakis, Spyridon Song, Houbing Jadoon, Muhammad Mohsin Abbas, Safia Farouk, Ahmed

【Source】IEEE INTERNET OF THINGS JOURNAL CCF-C

【影响因子】10.238

【主题类别】

区块链技术-协同技术-物联网

【Abstract】Cyber-physical systems (CPS) connected in the form of Internet of Things (IoT) are vulnerable to various security threats, due to the infrastructure-less deployment of IoT devices. Device-to-Device (D2D) authentication of these networks ensures the integrity, authenticity, and confidentiality of information in the deployed area. The literature suggests different approaches to address security issues in CPS technologies. However, they are mostly based on centralized techniques or specific system deployments with a higher cost of computation and communication. It is therefore necessary to develop an effective scheme that can resolve the security problems in CPS technologies of IoT devices. In this article, a lightweight hash media access control destination sequence distance vector (Hash-MAC-DSDV) routing scheme is proposed to resolve authentication issues in CPS technologies, connected in the form of IoT networks. For this purpose, a CPS of IoT devices (multi-WSNs) is developed from the local chain and public chain, respectively. The proposed scheme ensures D2D authentication by the Hash-MAC-DSDV mutual scheme, where the MAC addresses of individual devices are registered in the first phase and advertised in the network in the second phase. The proposed scheme allows legitimate devices to modify their routing table and unicast the one-way hash authentication mechanism to transfer their captured data from the source toward the destination. Our evaluation results demonstrate that Hash-MAC-DSDV outweighs the existing schemes in terms of attack detection, energy consumption, and communication metrics.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Authentication; Internet of Things; Security; Wireless sensor networks; Blockchain; Device-to-device communication; Computer science; Device-to-Device (D2D) authentication; hash media access control destination sequence distance vector (Hash-MAC-DSDV); Internet of Things (IoT); local and public chains; security

【发表时间】2022

【收录时间】2022-11-20

【文献类型】 实证数据

【DOI】 10.1109/JIOT.2021.3083731

【Author】 Zhang, Yan Li, Bing Wu, Jiaxin Liu, Bo Chen, Rui Chang, Jinke

【Source】IEEE INTERNET OF THINGS JOURNAL CCF-C

【影响因子】10.238

【主题类别】

区块链技术-核心技术-隐私保护

【Abstract】Industrial Internet of Things (IIoT) has emerged as a prospective technology that improves the productivity and automation level for industrial applications. Devices from cooperative IIoT domains will communicate and collaborate on the increasingly complicated manufacturing tasks. To secure cross-domain device collaborations, we propose combining the blockchain with multifactor authentication. Because the multifactor authentication conforms to IIoT devices' operation modes and brings higher security levels, and the blockchain technology contributes to building trust among different domains. However, this combined usage still has limitations in terms of the potential loss of factor attack, the storage overhead on the blockchain, and the contradiction between efficiency and privacy preservation. Motivated by these facts, in this article, we develop a privacy-preserving blockchain-based multifactor device authentication protocol for cross-domain IIoT. Specifically, multiple factors are additionally encoded by the hardware fingerprint into random numbers, before being transformed into key materials. The blockchain only stores each domain's dynamic accumulator, which accumulates derived key materials for devices, thereby reducing the overhead. Moreover, the on-chain accumulator is leveraged to efficiently verify the unlinkable identities of cross-domain IIoT devices. The security of our protocol is formally proved, and the security features and functionalities are, respectively, discussed. A proof-of-concept prototype was implemented to prove the efficiency and reliability. The comparison results indicate that the on-chain storage is greatly reduced. Finally, the smart contract's performance was evaluated to show scalability.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchains; Industrial Internet of Things; Security; Protocols; Multi-factor authentication; Public key; Privacy; Blockchain; cross-domain IIoT; Industrial Internet of Things (IIoT); multifactor authentication; security and privacy

【发表时间】2022

【收录时间】2022-11-20

【文献类型】 实证数据

【DOI】 10.1109/JIOT.2022.3176192

【Author】 Lopez, Hector K. Zilouchian, Ali

【Source】ENERGY

【影响因子】8.857

【主题类别】

区块链应用-实体经济-能源领域

【Abstract】This paper reviews a peer-to-peer energy market for prosumers of a regulated utility. Utilities pay retail prices to prosumers regardless of demand, forcing utilities to pass the cost of distribution to other consumers. As pro-sumers grow in numbers, utilities need a better compensation method. A real-time peer-to-peer energy market application may provide higher incentives. Utilities adopt the service because it would allow for compensation of overhead. By including the utility, a micro-grid is not needed for a peer-to-peer market. The prosumer com-munity can be virtual. The proposed implementation can become an intermediary step to decentralized energy markets. The application shall leverage the real-time demand of consumers and adjust payment instantly to prosumers that can meet that demand. A shared cloud account can allow the community to manage the appli-cation and create transparency and trust.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Peer-to-Peer; Energy; Solar; NRG-X-change; Renewables; Photo-voltaic; Micro-grid; Blockchain; Smart metering; Florida; Net metering

【发表时间】2023

【收录时间】2022-11-20

【文献类型】 实证数据

【DOI】 10.1016/j.energy.2022.125563

【Author】 Chen, Junbao Xue, Jingfeng Wang, Yong Huang, Lu Baker, Thar Zhou, Zhixiong

【Source】EXPERT SYSTEMS WITH APPLICATIONS CCF-C

【影响因子】8.665

【主题类别】

区块链应用-实体经济-工业领域

【Abstract】Federated learning enables data owners to jointly train a neural network without sharing their personal data, which makes it possible to share sensitive data generated from various Industrial Internet of Things (IIoT) devices. However, in traditional federated learning, the user directly sends its parameters to the server, which increases the risk of privacy leakage. To solve this problem, several privacy-preserving solutions have been proposed. However, most of them either reduce model accuracy or increase computation and communication overhead. In addition, federated learning is still exposed to the risk of model tampering, which may impair model accuracy. In this paper, we propose PPTFL, a Privacy-Preserving and Traceable Federated Learning framework with efficient performance. Specifically, we first propose a Hierarchical Aggregation Federated Learning (HAFL) to protect privacy with low overhead, which is suitable for IIoT scenarios. Then, we combine federated learning with blockchain and IPFS, which makes the parameters traceable and tamper-proof. The extensive experiments demonstrate the practical performance of PPTFL.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Hierarchical aggregation; Federated learning; Privacy protection; Blockchain

【发表时间】2023

【收录时间】2022-11-20

【文献类型】 实证数据

【DOI】 10.1016/j.eswa.2022.119036

【Author】 Felizardo, Leonardo Kanashiro Lima Paiva, Francisco Caio Graves, Catharine de Vita Matsumoto, Elia Yathie Reali Costa, Anna Helena Del-Moral-Hernandez, Emilio Brandimarte, Paolo

【Source】EXPERT SYSTEMS WITH APPLICATIONS CCF-C

【影响因子】8.665

【主题类别】

区块链治理-市场治理-区块链金融监管

【Abstract】The interdisciplinary relationship between machine learning and financial markets has long been a theme of great interest among both research communities. Recently, reinforcement learning and deep learning methods gained prominence in the active asset trading task, aiming to achieve outstanding performances compared with classical benchmarks, such as the Buy and Hold strategy. This paper explores both the supervised learning and reinforcement learning approaches applied to active asset trading, drawing attention to the benefits of both approaches. This work extends the comparison between the supervised approach and reinforcement learning by using state-of-the-art strategies with both techniques. We propose adopting the ResNet architecture, one of the best deep learning approaches for time series classification, into the ResNet-LSTM actor (RSLSTM-A). We compare RSLSTM-A against classical and recent reinforcement learning techniques, such as recurrent reinforcement learning, deep Q-network, and advantage actor-critic. We simulated a currency exchange market environment with the price time series of the Bitcoin, Litecoin, Ethereum, Monero, Nxt, and Dash cryptocurrencies to run our tests. We show that our approach achieves better overall performance, confirming that supervised learning can outperform reinforcement learning for trading. We also present a graphic representation of the features extracted from the ResNet neural network to identify which type of characteristics each residual block generates.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Deep neural network; Reinforcement learning; Stock trading; Time series classification; Cryptocurrencies

【发表时间】2022

【收录时间】2022-11-20

【文献类型】 实证数据

【DOI】 10.1016/j.eswa.2022.117259

【Author】 Cevik, Emrah Ismail Gunay, Samet Zafar, Muhammad Wasif Destek, Mehmet Akif Bugan, Mehmet Fatih Tuna, Fatih

【Source】RESOURCES POLICY

【影响因子】8.222

【主题类别】

区块链应用-虚拟经济-金融领域

【Abstract】The purpose of this study is to examine the interconnectedness between DeFi and natural resource assets in terms of return and volatility spillovers, as well as the effectiveness of hedging, utilizing the time and frequency domain causality test and the cross-quantilogram approach. To this end, we take into account the ChainLink (LINK) and Maker (MKR) prices for the DeFi market and use crude oil (WTI) and gold prices as proxies for the natural resources market. For this purpose, we observe the daily period from March 14, 2018, to August 15, 2022, in order to evaluate the portfolio diversification benefits during the Covid-19 epidemic. The findings from the time and frequency domain causality test reveal that the price and risk structure of natural resources such as crude oil and gold are influenced by digital finance instruments, particularly during times of crisis. Moreover, the results of the cross-quantilogram approach indicate that the significant cross-correlations between DeFi tokens and natural resource markets during bearish market periods are generally negative therefore DeFi tokens can provide effective hedging for gold and crude oil investors.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Digital finance; DeFi tokens; Oil; Gold; Portfolio diversification

【发表时间】2022

【收录时间】2022-11-20

【文献类型】 实证数据

【DOI】 10.1016/j.resourpol.2022.103081

【Author】 Yakubu, Abukari Mohammed Chen, Yi Ping Phoebe

【Source】FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE

【影响因子】7.307

【主题类别】

区块链应用-实体经济-科研领域

【Abstract】Genomic data repositories are rapidly growing due to the decline in the cost of DNA sequencing. This has increased the demand from stakeholders such as researchers to analyze these datasets to advance areas in biomedical research. Genomic datasets are mostly maintained by third-party directto-consumer (DTC) genomic companies who operate a business model of collecting DNA data from their customers and selling them to pharmaceutical companies. This puts the privacy of their customers at risk since each individual's human genome is unique. In addition, customers lose ownership of and access to their genomic data to DTCs and DTCs do not share profits from data sales with them. In this paper, we propose a system based on blockchain technology and homomorphic computation to address the aforementioned problems. We use blockchain transactions and smart contracts to allow genomic data owners (DOs) to have control of their data and sell access to it, and homomorphic computation with secure two-party protocol to enable genomic data users (DUs) to run queries to securely discover DOs of interest. We further optimize the query response time by proposing an approach based on genomic data partitions, binary search trees and bloom filters to reduce the search space. We also propose a blockchain penalty mechanism to encourage parties to behave honestly to avoid malicious behaviors such as uploading fake or non-human genomic data. We conduct our experiments on real genomic datasets and demonstrate that our proposed scheme allows DOs to control access to their data and is feasible and efficient in terms of computation cost, query response time and scalability. (C) 2022 Elsevier B.V. All rights reserved.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Genome; Variant discovery; Blockchain; Smart contracts; Access control; Privacy-preserving

【发表时间】2022

【收录时间】2022-11-20

【文献类型】 实证数据

【DOI】 10.1016/j.future.2022.07.012

【Author】 Jin, Hyungrok Hwang, Jaehee Luo, Bingqin Kim, Taeyeon Sung, Yongjun

【Source】CYBERPSYCHOLOGY BEHAVIOR AND SOCIAL NETWORKING

【影响因子】6.135

【主题类别】

区块链应用-虚拟经济-元宇宙

【Abstract】The Metaverse is an important virtual venue in people's daily lives. This study examined whether pro-environmental behaviors in the Metaverse with a self-customized avatar lead to licensing effects, thereby reducing pro-environmental intention in reality. In addition, the study examined the mediating effect of self-presence on the relationship between avatar customization and pro-environmental behavior. A laboratory experiment was conducted using ZEPETO, a Metaverse platform. A total of 60 participants were randomly assigned to the self-customized avatar condition or the assigned avatar condition, and they engaged in pro-environmental behaviors on the Metaverse platform. Participants with self-customized avatars had less intention to engage in pro-environmental behavior in reality after engaging in pro-environmental behavior in the Metaverse than those with assigned avatars. Furthermore, self-presence partially mediated the relationship between avatar customization and pro-environmental intention.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Metaverse; licensing effect; avatar; pro-environmental behavior

【发表时间】

【收录时间】2022-11-20

【文献类型】 实证数据

【DOI】 10.1089/cyber.2021.0320

【Author】 Ning, Zhaolong Sun, Shouming Wang, Xiaojie Guo, Lei Guo, Song Hu, Xiping Hu, Bin Kwok, Ricky Y. K.

【Source】IEEE TRANSACTIONS ON MOBILE COMPUTING CCF-A

【影响因子】6.075

【主题类别】

区块链应用-实体经济-交通领域

【Abstract】Intelligent Transportation System (ITS) is critical to cope with traffic events, e.g., traffic jams and accidents, and provide services for personal traveling. However, existing researches have not jointly considered the user data safety, utility and system latency comprehensively, to the best of our knowledge. Since both safe and efficient transmissions are significant for ITS, we construct a blockchain-enabled crowdsensing framework for distributed traffic management. First, we illustrate the system model and formulate a multi-objective optimization problem. Due to its complexity, we decompose it into two subproblems, and propose the corresponding schemes, i.e., a Deep Reinforcement Learning (DRL)-based algorithm and a DIstributed Alternating Direction mEthod of Multipliers (DIADEM) algorithm. Extensive experiments are carried out to evaluate the performance of our solutions, and experimental results demonstrate that the DRL-based algorithm can legitimately select active miners and transactions to make a satisfied trade-off between the blockchain safety and latency, and the DIADEM algorithm can effectively select task computation modes for vehicles in a distributed way to maximize their social welfare.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchain; Safety; Optimization; Task analysis; Crowdsensing; Servers; Roads; Distributed traffic management; blockchain; deep reinforcement learning; vehicular crowdsensing; multi-objective optimization

【发表时间】2022

【收录时间】2022-11-20

【文献类型】 实证数据

【DOI】 10.1109/TMC.2021.3079984

【Author】 Andrade, Maira Sharman, Steve Xiao, Leon Y. Newall, Philip W. S.

【Source】PSYCHOLOGY OF ADDICTIVE BEHAVIORS

【影响因子】4.044

【主题类别】

区块链治理-市场治理-数字货币

【Abstract】Objective: Online gambling has increased the accessibility and range of gambling products available to people all over the world. This trend has been particularly noticeable in the United Kingdom. Cryptocurrency-based gambling is a new, largely unregulated, way to gamble online, which uses mostly anonymous blockchain-based technologies, such as Bitcoin. The present research investigated consumer protection features of 40 frequently visited and U.K.-accessible cryptocurrency-based online gambling operators. Method: A content analysis was performed by visiting all 40 cryptocurrency-based online operators and recording their safer gambling and consumer protection practices. Coded features included aspects of the sign-up process, features of any safer gambling pages, customer support practices, and Identity verification. Results: Results revealed significant failings in the account registration process; none of the operators verified the identity of new users, and 35% required only an email or no personal information for sign-up. Overall, 37.5% of operators offered no safer gambling tools and a further 20% offered only one. Additionally, 64.7% of operators continued to email promotional material after being informed of a user's impaired control when gambling. Less than half of the analyzed operators held a valid license (47.5%), and none of the operators with an available deposit page required identity verification before enabling deposits. Conclusions: These results highlight the potential risks for young and vulnerable individuals, especially when a lack of identity verification is paired with the inherent anonymity of cryptocurrencies. Furthermore, it emphasizes the need for greater policy and research attention toward cryptocurrency-based online gambling. Public Health Significance Statement Cryptocurrency-based gambling is a fast-growing gambling format, and top operators are heavily investing in consumer reach through sports advertisements. However, information on the safer gambling and consumer protection practices of frequently visited operators is nonexistent. The findings in this study showed significant failings in consumer protection and safer gambling practices, which suggest an increased risk of gambling-related harm in cryptocurrency-based gambling.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】crypto gambling; online betting; safer gambling; responsible gambling; regulation

【发表时间】

【收录时间】2022-11-20

【文献类型】 实证数据

【DOI】 10.1037/adb0000885

【Author】 Alanazi, Jazem Mutared AlZubi, Ahmad Ali

【Source】INTELLIGENT AUTOMATION AND SOFT COMPUTING

【影响因子】3.401

【主题类别】

区块链应用-实体经济-其他

【Abstract】Accounting Information System (AIS), which is the foundation of any enterprise resource planning (ERP) system, is often built as centralized system. The technologies that allow the Internet-of-Value, which is built on five aspects that are network, algorithms, distributed ledger, transfers, and assets, are based on blockchain. Cryptography and consensus protocols boost the blockchain platform implementation, acting as a deterrent to cyber-attacks and hacks. Blockchain platforms foster innovation among supply chain participants, resulting in ecosystem development. Traditional business processes have been severely disrupted by blockchains since apps and transactions that previously required centralized structures or trusted third-parties to authenticate them may now function in a decentralized manner with the same level of assurance. Because a blockchain split in AIS may easily lead to double-spending attacks, reducing the likelihood of a split has become a very important and difficult research subject. Reduced block relay time between the nodes can minimize the block propagation time of all nodes, resulting in better Bitcoin performance. In this paper, three problems were addressed on transaction and block propagation mechanisms in order to reduce the likelihood of a split. A novel algorithm for blockchain is proposed to reduce the total propagation delay in AIS transactions. Numerical results reveal that, the proposed algorithm performs better and reduce the transaction delay in AIS as compared with existing methods.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Information systems; internal control; blockchain; digital transactions

【发表时间】2023

【收录时间】2022-11-20

【文献类型】 实验仿真

【DOI】 10.32604/iasc.2023.029181

【Author】 Yuan, Wen-Xin Yan, Bin Li, Wen Hao, Liu-Yao Yang, Hong-Mei

【Source】MULTIMEDIA TOOLS AND APPLICATIONS CCF-C

【影响因子】2.577

【主题类别】

区块链应用-实体经济-医疗领域

【Abstract】The patient's medical health record (PMHR) has always provided a large amount of research data to medical institutions and pharmaceutical companies, etc., and has contributed to the development in medical research. However, such PMHR data contains the patient's personal privacy and should be shared under the control of the patients, not the hospital where this data is acquired. In order to protect the privacy of PMHR data while realizing efficient data sharing, this paper proposes a blockchain-based sharing and protection scheme. In this solution, the PMHR data are encrypted and stored in a cloud server, which is equipped with an access control scheme implemented as a smart contract on a blockchain. Different from previous works, in order to ensure efficient access and reduce the workload of patients, the types of users who can apply for access are limited to hospitals and pharmaceutical companies. In order to resist the potential Man-in-the-middle (MITM) attack, we have introduced an improved proxy re-encryption scheme to ensure the secrecy of PMHR data while reducing the computational complexity. The whole system is implemented using Solidity and tested on 10 nodes for function verification. Experimental result shows that the proposed system is more efficient than previous systems. Security under the MITM attack is also ensured by security analysis.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Medical health records; Blockchain; Proxy re-encryption

【发表时间】

【收录时间】2022-11-20

【文献类型】 实证数据

【DOI】 10.1007/s11042-022-14023-3

【Author】 Zhou, Binbin

【Source】MOBILE INFORMATION SYSTEMS

【影响因子】1.863

【主题类别】

区块链应用-实体经济-教育领域

【Abstract】Metaverse is the future of the Internet and integrates a variety of information technologies. It leads future education trends and brings profound changes to education. On the basis of analysis of the development trend of smart education and the connotation and action mechanism of edu-metaverse in the view of metaverse, this paper structures the smart education ecosystem, builds the scenario and modular smart learning space of three education scenarios of resource collaborative interaction, virtuality-reality integration experience, and ubiquitous spatial inquiry by using the six core technologies, and forms the new education mode of virtuality-reality symbiosis, trans-spatial fusion, and collaborative inquiry. Then, it verifies the application effect by AHP. Finally, it creates the smart education ecosystem of "four ecology integration"-resource ecology, interaction ecology, space ecology, and collaboration ecology, which accelerates the organic integration of metaverse and smart education and provides theoretical basis and reference for the new application of future education.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】

【发表时间】2022

【收录时间】2022-11-20

【文献类型】 实证数据

【DOI】 10.1155/2022/1938329