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A survey on the adoption of blockchain in IoT:challenges and solutions

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Blockchain(Research and Applications) 2021年第2期2卷 1-49页

作者： Md Ashraf Uddin Andrew Stranieri Iqbal Gondal Venki Balasubramanian internet commerce security laboratory Federation University AustraliaMount HelenBallaratVIC3350Australia

Conventional internet of Things(IoT)ecosystems involve data streaming from sensors,through Fog devices to a centralized Cloud *** that arise include privacy concerns due to third party management of Cloud servers,single points of failure,a bottleneck in data flows and difficulties in regularly updating firmware for millions of smart devices from a point of security and maintenance *** technologies avoid trusted third parties and safeguard against a single point of failure and other *** has inspired researchers to investigate blockchain’s adoption into IoT *** this paper,recent state-of-the-arts advances in blockchain for IoT,blockchain for Cloud IoT and blockchain for Fog IoT in the context of eHealth,smart cities,intelligent transport and other applications are ***,research gaps and potential solutions are also presented.

关键词： Blockchain technology Consensus mechanism Blockchain cryptographic primitives healthcare Patient monitoring Cloud of Things internet of Things Fog of Things Software defined network Blockchain applications

Correlations multiplexing for link prediction in multidimensional network spaces

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Science China(Information Sciences) 2018年第11期61卷 48-66页

作者： Yunpeng XIAO Xixi LI Yuanni LIU Hong LIU Qian LI Chongqing Engineering laboratory of internet and Information security Chongqing University of Posts and Telecommunications

In social networks, link establishment among users is affected by diversity correlations. In this paper, we study the formation of links, map correlations into multidimensional network spaces and apply their behavioral and structural features to the problem of link prediction. First, by exploring user behavioral correlation and network structural correlation, we map them into three network spaces: following space, interaction space and structure space. With a hierarchical process, the coupling relationship between the spaces can be reduced and we can analyze the correlation in each space separately. Second, by taking advantage of the latent Dirichlet allocation(LDA) topic model for dealing with the polysemy and synonym problems, the traditional text modeling method is improved by Gaussian weighting and applied to user behavior *** this way, the expression ability of topics can be enhanced, and improved topic distribution of user behavior can be obtained to mine user correlations in the following space and the interaction space. Moreover, the method can be extended using the hidden naive Bayesian algorithm which is good at reducing attribute independence. By quantifying the dependencies between common neighbors, we can analyze user correlations in the structure space and multiplex the correlations of the other two spaces to link prediction. The experimental results indicate that the method can effectively improve link prediction performance.

关键词： social networks multidimensional network spaces link prediction LDA hidden naive Bayes

Who will retweet? A prediction method for social hotspots based on dynamic tensor decomposition

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Science China(Information Sciences) 2018年第9期61卷 297-299页

作者： Yunpeng XIAO Xiaojuan LI Shasha YANG Yanbing LIU Chongqing Engineering laboratory of internet and Information security Chongqing University of Posts and Telecommunications

With the development of Web 2.0,the emergence of blogs,forums makes the internet to maintain substantial amounts of user behavioral *** data are rich and valuable,and mining useful information from massive data has be... 详细信息

关键词： A prediction method for social hotspots based on dynamic tensor decomposition Who will retweet

Analysis of Review Helpfulness Based on Consumer Perspective

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Tsinghua Science and Technology 2015年第3期20卷 293-305页

作者： Yuanlin Chen Yueting Chai Yi Liu Yang Xu National Engineering laboratory for E-commerce Technologies Tsinghua University DNSLAB China Internet Network Information Center

When consumers make purchase decisions, they generally refer to the reviews generated by other consumers who have already purchased similar products in order to get more information. Online transaction platforms provide a highly convenient channel for consumers to generate and retrieve product reviews. In addition, consumers can also vote reviews perceived to be helpful in making their decision. However, due to diverse characteristics, consumers can have different preferences on products and reviews. Their voting behavior can be influenced by reviews and existing review votes. To explore the influence mechanism of the reviewer, the review, and the existing votes on review helpfulness, we propose three hypotheses based on the consumer perspective and perform statistical tests to verify these hypotheses with real review data from Amazon. Our empirical study indicates that review helpfulness has significant correlation and trend with reviewers, review valance, and review votes. In this paper, we also discuss the implications of our findings on consumer preference and review helpfulness.

关键词： consumer preference online decision making review helpfulness behavior analysis

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Study on moisture absorption characteristics of glass fibrereinforced epoxy resin material for composite insulators based on the 3D-Fick model

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High Voltage 2024年第4期9卷 888-901页

作者： Yuming Zhang Yunpeng Liu Sizu Hou Jianghai Geng Ping Wang Hebei Provincial Key laboratory of Power Transmission Equipment security Defense North China Electric Power UniversityBaodingChina Hebei Key laboratory of Power internet of Things Technology BaodingChina

Long-term exposure to moisture leads to a gradual deterioration of performance and reduced service life of glass fibre-reinforced epoxy resin(GFRP)material in composite ***,it is necessary to analyse the moisture absorption characteristics of GFRP material and the evolution of damage to their internal interface *** absorption tests on GFRP rod material used in composite insulators to obtain their three-dimensional diffusion coefficients are *** force microscopy was then employed to obtain the composite material system's fibre/matrix interfacial phase ***,a finite element model incorporating representative volume elements with interfacial phases and a mesoscale transient moisture absorption finite element model for the composite material was ***,the moisture absorption characteristics of GFRP material and the evolution of damage to the interfacial phase under thermal-humidity cycling conditions were *** results showed that the diffusion coefficient along the fibre direction in GFRP material was higher than that in the perpendicular *** moisture diffusion finite element model,incorporating an anisotropic interfacial phase,fitted the anisotropic diffusion coefficients of GFRP material more *** moisture invaded the GFRP material,the mismatch stresses continuously increased during the moisture ***,the non-uniform arrangement of fibres resulted in uneven distribution of moistureinduced stresses inside the material,leading to higher mismatch stresses in areas with dense fibre arrangements in the *** high and low humidity cycles led to the development of micro-cracks,micro-porosity,and interface debonding along the fibre direction at the GFRP material interfaces,thereby affecting the anisotropic moisture absorption characteristics of the *** findings of this study provide valuable insights into the mechanisms underlying the

关键词： composite fibre moisture

EVchain: An Anonymous Blockchain-Based System for Charging–Connected Electric Vehicles

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Tsinghua Science and Technology 2021年第6期26卷 845-856页

作者： Shiyuan Xu Xue Chen Yunhua He North China University of Technology Beijing 100144China Beijing Key laboratory of internet of Things security Institute of Information EngineeringChinese Academy of Sciences(CAS)Beijing 100093China

Purchases of electric vehicles have been increasing in recent years. These vehicles differ from traditional fossil-fuel-based vehicles especially in the time consumed to keep them running. Electric-Vehicle-charging Service Providers(EVSPs) must arrange reasonable charging times for users in advance. Most EVSP services are based on third-party platforms, but reliance on third-party platforms creates a lack of security, leaving users vulnerable to attacks and user-privacy leakages. In this paper, we propose an anonymous blockchain-based system for charging-connected electric vehicles that eliminates third-party platforms through blockchain technology and the establishment of a multi-party security system between electric vehicles and EVSPs. In our proposed system, digital certificates are obtained by completing distributed Public Key Infrastructure(distributed-PKI) identity registration,with the user registration kept separate from the verification process, which eliminates dependence on the EVSP for information security. In the verification process, we adopt smart contracts to solve problems associated with centralized verification and opaque services. Furthermore, we utilize zero-knowledge proof and ring-signature superposition to realize completely anonymous verification, which ensures undeniability and unforgeability with no detriment to anonymity. The evaluation results show that the user anonymity, information authenticity, and system security of our system fulfill the necessary requirements.

关键词： blockchain Electric Vehicles(EV) zero knowledge proof distributed Public Key Infrastructure(distributed-PKI) ring signature smart contract

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An efficient hybrid system for anomaly detection in social networks

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Cybersecurity 2021年第1期4卷 136-146页

作者： Md.Shafiur Rahman Sajal Halder MdAshraf Uddin Uzzal Kumar Acharjee Department of Computer Science and Engineering Dhaka International UniversityDhakaBangladesh Department of Computer Science and Engineering Jagannath UniversityDhakaBangladesh Department Computer Science and Information Technology RMIT UniversityMelbourneAustralia internet commerce security laboratory Federation University AustraliaBallarat VIC 3350Australia

Anomaly detection has been an essential and dynamic research area in the data mining.A wide range of applications including different social medias have adopted different state-of-the-art methods to identify anomaly for ensuring user’s security and *** social network refers to a forum used by different groups of people to express their thoughts,communicate with each other,and share the content *** social networks also facilitate abnormal activities,spread fake news,rumours,misinformation,unsolicited messages,and propaganda post malicious ***,detection of abnormalities is one of the important data analysis activities for the identification of normal or abnormal users on the social *** this paper,we have developed a hybrid anomaly detection method named DT-SVMNB that cascades several machine learning algorithms including decision tree(C5.0),Support Vector Machine(SVM)and Naïve Bayesian classifier(NBC)for classifying normal and abnormal users in social *** have extracted a list of unique features derived from users’profile and *** two kinds of dataset with the selected features,the proposed machine learning model called DT-SVMNB is *** model classifies users as depressed one or suicidal one in the social *** have conducted an experiment of our model using synthetic and real datasets from social *** performance analysis demonstrates around 98%accuracy which proves the effectiveness and efficiency of our proposed system.

关键词： Anomaly Detection Machine Learning Hybrid Anomaly Detection Social Networks

A comparative survey of SSVEP recognition algorithms based on template matching of training trials

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International Journal of Intelligent Computing and Cybernetics 2023年第1期16卷 46-67页

作者： Tian-Jian Luo College of Computer and Cyber security Fujian Normal UniversityFuzhouChina Digital Fujian internet-of-Thing laboratory of Environmental Monitoring Fujian Normal UniversityFuzhouChina

Purpose-Steady-state visual evoked potential(SSVEP)has been widely used in the application of electroencephalogram(EEG)based non-invasive brain computer interface(BCI)due to its characteristics of high accuracy and information transfer rate(ITR).To recognize the SSVEP components in collected EEG trials,a lot of recognition algorithms based on template matching of training trials have been proposed and applied in recent *** this paper,a comparative survey of SSVEP recognition algorithms based on template matching of training trails has been ***/methodology/approach-To survey and compare the recently proposed recognition algorithms for SSVEP,this paper regarded the conventional canonical correlated analysis(CCA)as the baseline,and selected individual template CCA(ITCCA),multi-set CCA(MsetCCA),task related component analysis(TRCA),latent common source extraction(LCSE)and a sum of squared correlation(SSCOR)for ***-For the horizontal comparative of the six surveyed recognition algorithms,this paper adopted the“Tsinghua JFPM-SSVEP”data set and compared the average recognition performance on such data *** comparative contents including:recognition accuracy,ITR,correlated coefficient and R-square values under different time duration of the SSVEP stimulus *** on the optimal time duration of stimulus presentation,the author has also compared the efficiency of the six compared *** measure the influence of different parameters,the number of training trials,the number of electrodes and the usage of filter bank preprocessing were compared in the ablation ***/value-Based on the comparative results,this paper analyzed the advantages and disadvantages of the six compared SSVEP recognition algorithms by considering application scenes,realtime and computational ***,the author gives the algorithms selection range for the recognition of real-world online SSVEP-BCI.

关键词： Non-invasive brain-computer interface EEG signals Template matching of training trials Steadystate visual evoked potential Optimal projection vector

Multifactor-influenced Reliability-constrained Reserve Expansion of Integrated Electricity-gas Systems Considering Failure Propagation

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CSEE Journal of Power and Energy Systems 2023年第6期9卷 2236-2250页

作者： Minglei Bao Xiaocong Sun Yi Ding Chengjin Ye Changzheng Shao Sheng Wang Yonghua Song the College of Electrical Engineering Zhejiang UniversityHangzhou 310027China the State Key laboratory of Power Transmission Equipment and System security at Chongqing University Chongqing 400044China the State Key laboratory of internet of Things for Smart City University of MacaoMacao 999078China

With the increasing interactions between natural gas systems(NGS)and power systems,component failures in one system may propagate to the other one,threatening reliable operation of the whole *** to neglect of such cross-sectorial failure propagation in integrated electricity-gas systems(IEGSs),traditional economy-oriented reserve expansion models may lead to unreasonable planning *** order to address this,an innovative reserve expansion model is proposed to determine the allocation of energy production components through the harmonization between costs and ***,novel multifactor-influenced reliability indices are defined con-sidering synthetic effects of multiple uncertainties,including failure propagation,load uncertainties and generation *** reliability index formulation,contribution of failure propagation on system reliability is analytically *** avoid high computational complexity,the fuzzy set theory is combined with conventional methods,e.g.,Monte-Carlo simulation technique to reduce numerous contingency *** contingency states are aggregated into several clusters represented by a fuzzy *** effectively solve the planning model,a decomposition approach is introduced and applied to decompose the original problem into a master problem and two correlated reliability *** studies show the proposed model can plan reasonable reserves to guarantee reliability levels of IEGSs considering failure propagation.

关键词： Cross-sectorial 1 failure propagation fuzzy model integrated electricity-gas systems long-term reserve planning reliability