Titlebook: Blockchain and Trustworthy Systems; 5th International Co Jiachi Chen,Bin Wen,Ting Chen Conference proceedings 2024 The Editor(s) (if applic

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Dynamic Computation Offloading Leveraging Horizontal Task Offloading and Service Migration in Edge N the intermediate node selection issue are expounded as a multi-faceted .arkov .ecision .rocess (.) realm, the boundaries of which are contingent on the burden placed upon the incumbent network. As a means of diminishing the expansiveness of the aforementioned . sphere and facilitating prompt judgme

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Securing Blockchain Using Propagation Chain Learningven the-state-of-art smart contract vulnerability detection methods on a large-scale smart contract dataset based on the Solidity language. The experimental results show that CuVuD’s effectiveness in detecting smart contract vulnerabilities is significantly higher than seven the-state-of-art smart c

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Research on Comprehensive Blockchain Regulation and Anti-fraud Systemkchain transaction patterns and detecting illegal transaction behavior using new heuristic learning methods and graph neural network methods to detect frequent frauds. The system monitors and detects fraudulent activities such as phishing, ICO, price manipulation, money laundering, and illegal fundr

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Smart Contract Vulnerability Detection Methods: A Surveyanalysis are conducted on the input code categories, vulnerability types, and classification output formats of each method. Finally, based on the summary of existing research on smart contract vulnerability detection, the challenges in the field of smart contract vulnerability detection are discusse

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,Comments on “Law as a Capital Good”,acy (over 90%). Through our large-scale study, we have identified 69, 148 highly suspicious scam messages, relating to 8, 247 blockchain addresses. By tracing the confirmed scam addresses, we further identify a cumulative illicit income of around 900 ETH. Our findings should help the blockchain comm