Blockchain, Metaverse and Trustworthy Systems

.- Blockchain and Data Mining. .- Intrusion Anomaly Detection with Multi-Transformer. .- A Federated Learning Method Based on Linear Probing and Fine-Tuning. .- Facilitating Feature and Topology Lightweighting: An Ethereum Transaction Graph Compression Method for Malicious Account Detection. .- A Secure Hierarchical Federated Learning Framework based on FISCO Group Mechanism. .- Research on Network Traffic Anomaly Detection Method Based on Deep Learning. .- Hyper-parameter Optimization and Proxy Re-encryption for Federated Learning. .- Data Security and Anomaly Detection. .- Exploring Embedded Content in the Ethereum Blockchain: Data Restoration and Analysis. .- Task Allocation and Process Optimization of Data, Information, Knowledge, and Wisdom (DIKW)-based Workflow Engine. .- Location Data Sharing Method Based on Blockchain and Attribute-Based Encryption. .- Implicit White-Box Implementations of Efficient Double-Block-Length MAC. .- A Survey on Blockchain Scalability. .- Supply Chain Financing Model Embedded with “Full-Process” Blockchain. .- Blockchain Performance Optimization. .- ReCon: Faster Smart Contract Vulnerability Detection by Reusable Symbolic Execution Tree. .- SVD-SESDG: Smart Contract Vulnerability  Detection Technology via Symbol Execution and  State Variable Dependency Graph. .- Dual-view Aware Smart Contract Vulnerability Detection for Ethereum. .- Blockchain Layered Sharding Algorithm Based on Transaction Characteristics. .- An Empirical Study on the Performance of EVMs and Wasm VMs for Smart Contract Execution. .- Ponzi Scheme Detection in Smart Contracts Using Heterogeneous Semantic Graph.