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Titlebook: Blockchain and Trustworthy Systems; Second International Zibin Zheng,Hong-Ning Dai,Benhui Chen Conference proceedings 2020 Springer Nature

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期刊全稱Blockchain and Trustworthy Systems
期刊簡稱Second International
影響因子2023Zibin Zheng,Hong-Ning Dai,Benhui Chen
視頻videohttp://file.papertrans.cn/190/189233/189233.mp4
學(xué)科分類Communications in Computer and Information Science
圖書封面Titlebook: Blockchain and Trustworthy Systems; Second International Zibin Zheng,Hong-Ning Dai,Benhui Chen Conference proceedings 2020 Springer Nature
影響因子This book constitutes the thoroughly refereed post conference papers of the Second International Conference on Blockchain and Trustworthy Systems, Blocksys 2020, held in Dali, China*, in August 2020..The 42 full papers and the 11 short papers were carefully reviewed and selected from 100 submissions. The papers are organized in topical sections:?theories and algorithms for blockchain,?performance optimization of blockchain,?blockchain security and privacy,?blockchain and cloud computing,?blockchain and internet of things,?blockchain and mobile edge computing,?blockchain and smart contracts,?blockchain and data mining,?blockchain services and applications,?trustworthy system development..*The conference was held virtually due to the COVID-19 pandemic..
Pindex Conference proceedings 2020
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J?rn Peter Hiekel,Christian Utzices from being selected. For the second phase, we devise a participant-selection algorithm that enables the FL server to select the appropriate group of devices for each round of FL-training. We believe that our study can shed new light on the joint research of blockchain and federated learning.
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J?rn Peter Hiekel,Christian Utz, we carefully designed a trading contract to ensure a fair and transparent trading process. In addition, we build a matching score calculation algorithm, according to which PSM. can determine the price for purchasing someone’s contact information. Finally, we develop a proof of concept prototype on
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Felix W?rner,Melanie Wald-Fuhrmannastly, based on the analysis of the Ether flow of the phishing scam cycle, we propose an improved Graph2Vec, and make classification prediction on the subgraphs we built. The experimental results show that our framework has achieved a great competitiveness in the final classification task, which als
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Felix W?rner,Melanie Wald-Fuhrmanne 0.98, 0.93 and 0.95 respectively by experiments. Smart Ponzi schemes hidden on Ethereum are detected effectively by the model. More importantly, the performance of model is guaranteed at any moment in the lifecycle, even at the birth of a smart Ponzi scheme.
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