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  <titleInfo>
    <title>Blockchain and Trustworthy Systems</title>
    <subTitle>5th International Conference, BlockSys 2023, Haikou, China, August 8–10, 2023, Proceedings, Part I</subTitle>
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    <namePart>Chen, Jiachi.</namePart>
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    <namePart>Wen, Bin.</namePart>
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    <namePart>Chen, Ting.</namePart>
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    <dateIssued encoding="marc">2024</dateIssued>
    <edition>1st ed. 2024.</edition>
    <issuance>monographic</issuance>
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    <extent>XIX, 299 p. 80 illus., 69 illus. in color. online resource.</extent>
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  <abstract>The two-volume set CCIS 1896 and 1897 constitutes the refereed post-conference proceedings of the 5th International Conference on Blockchain and Trustworthy Systems, BlockSys 2023, which took place in Haikou, China during August 8–10, 2023. The 45 revised full papers presented in these proceedings were carefully reviewed and selected from 93 submissions. The papers are organized in the following topical sections: Part I: Anomaly detection on blockchain; edge intelligence and metaverse services; blockchain system security; empirical study and surveys; federated learning for blockchain. Part II: AI for blockchain; blockchain applications; blockchain architecture and optimization; protocols and consensus.</abstract>
  <tableOfContents>Anomaly detection on blockchain -- Blockchain Scam Detection: State-of-the-art, Challenges, and Future Directions -- ScamRadar: Identifying Blockchain Scams When They are Promoting -- Based on Financial Characteristics to Capture the Source of Funds of the Ponzi Scheme on Ethereum with Graph Traversal Technology -- Based on Financial Characteristics to Capture the Source of Funds of the Ponzi Scheme on Ethereum with Graph Traversal Technology -- Edge Intelligence and Metaverse Services -- Dynamic Computation Offloading Leveraging Horizontal Task Offloading and Service Migration in Edge Networks -- Blockchain-Assisted Authentication and Key Agreement Protocol for Cloud-Edge Collaboration -- Towards Efficient and Privacy-preserving Hierarchical Federated Learning for Distributed Edge Network -- Blockchain System Security -- Securing Blockchain Using Propagation Chain Learning -- Privacy Protection Multi-copy Provable Data Possession supporting Data Reliability -- Research On Comprehensive Blockchain Regulation And Antifraud System -- Analysis of Peeling Chain Model in Bitcoin Mixing Service -- A Blockchain-based On-chain and Off-chain Dual-trusted Carbon Emission Trading System with Reputation Mechanism -- Empirical Study and Surveys -- Smart Contract Vulnerability Detection Methods: A Survey -- Who Needs the Most Research Effort? Investigating the Importance of Smart Contract Weaknesses -- A Survey on Blockchain Abnormal Transaction Detection -- A Systematic Literature Review on Smart Contract Vulnerability Detection by Symbolic Execution -- Sharding Technologies in Blockchain: Basics, State of the Art, and Challenges -- Federated Learning for Blockchain -- A Blockchain-enabled Decentralized Federated Learning System with Transparent and Open Incentive and Audit Contracts -- Blockchain-based Federated Learning for IoT Sharing: Incentive Scheme with Reputation Mechanism -- An Optimized Scheme of Federated Learning Based on Differential Privacy.</tableOfContents>
  <note type="statement of responsibility">edited by Jiachi Chen, Bin Wen, Ting Chen.</note>
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    <topic>Data protection</topic>
    <topic>Law and legislation</topic>
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    <topic>Artificial intelligence</topic>
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    <topic>Data structures (Computer science)</topic>
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    <topic>Artificial Intelligence</topic>
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    <topic>Data Structures and Information Theory</topic>
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    <topic>Operating Systems</topic>
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  <subject>
    <topic>Special Purpose and Application-Based Systems</topic>
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      <title>Communications in Computer and Information Science, 1896</title>
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  <identifier type="isbn">9789819981014</identifier>
  <identifier type="uri">https://doi.org/10.1007/978-981-99-8101-4</identifier>
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