Blockchain, Metaverse and Trustworthy Systems

This two-volume set CCIS 2264 and CCIS 2265 constitutes the refereed proceedings of the 6th International Conference on Blockchain and Trustworthy Systems, BlockSys 2024, held in Hangzhou, China, during July 12-14, 2024.

The 34 full papers presented in these two volumes were carefully reviewed and selected from 74 submissions. The papers are organized in the following topical sections:

Part I: Blockchain and Data Mining; Data Security and Anomaly Detection; Blockchain Performance Optimization.

Part II: Frontier Technology Integration; Trustworthy System and Cryptocurrencies; Blockchain Applications.

. - 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.