Description
Book Synopsis.- Blockchain and Cryptocurrencies.
.- EquinoxBFT: BFT Consensus for Blockchain Emergency Governance.
.- fFuzz: A State-aware Function-level Fuzzing Framework for Smart Contract Vulnerabilities Detection.
.- TraceBFT: Backtracking-based Pipelined Asynchronous BFT Consensus for High-Throughput Distributed Systems.
.- RADIAL: Robust Adversarial Discrepancy-aware Framework for Early Detection of Illicit Cryptocurrency Accounts.
.- Enhancing Private Signing Key Protection in Digital Currency Transactions Using Obfuscation.
.- AnsBridge: Towards Secure Cross-Chain Interoperability via Anonymous and Verifiable Validators.
.- TrustBlink: A zkSNARK-Powered On-Demand Relay for PoW Cross-Chain Verification With Low Cost.
.- R1-MFSol: a Smart Contract Vulnerability Detection Model Based on LLM and Multi-modal Feature Fusion.
.- No Place to Hide: An Efficient and Accurate Backdoor Detection Tool for Ethereum ERC-20 Smart Contracts.
.- System and Network Security.
.- Batch-oriented Element-wise Approximate Activation for Privacy-Preserving Neural Networks.
.- Social-Aware and Quality-Driven Incentives for Mobile Crowd-Sensing with Two-Stage Game.
.- A Distributed Privacy Protection Method for Crowd Sensing Based on Trust Evaluation.
.- DBG-LB: A Trustworthy and Efficient Framework for Data Sharing in the Internet of Vehicles.
.- Actions Speak Louder Than Words: Evidence-Based Trust Level Evaluation in Multi-Agent Systems.
.- Bridging the Interoperability Gaps Among Trusted Architectures in MCUs.
.- Security and Privacy of AI.
.- A Dropout-Resilient and Privacy-Preserving Framework for Federated Learning via Lightweight Masking.
.- AFedGAN: Adaptive Federated Learning with Generative Adversarial Networks for Non-IID Data.
.- OTTER: Optimized Training with Trustworthy Enhanced Replication via Diffusion and Federated VMUNet for Privacy-Aware Medical Segmentatio.
.- EAGLE: Ensemble Adaptive Graph Learning for Enhanced Ethereum Fraud Detection.
.- BR-CPPFL: A Blockchain-based Robust Clustered Privacy-preserving Federated Learning System.
.- Efficient Semi-asynchronous Federated Learning with Guided Selective Participation and Adaptive Aggregation.
.- Improving Byzantine-resilience in Federated Learning via Diverse Aggregation and Adaptive Variance Reduction.
.- Hierarchical Recovery of Convolutional Neural Networks via Self-Embedding Watermarking.
.- Personalized Federated Learning Algorithm Based on User Grouping and Group Signatures.
.- Machine Learning for Security.
.- SPCD: A Shot-Based Partial Copy Detection Method.
.- Bayesian-Adaptive Graph Neural Network for Anomaly Detection (BAGNN).
.- UzPhishNet Model for Phishing Detection.
.- CyberNER-LLM: Cyber Threat Intelligence Named Entity Recognition With Large Language Model.
.- Provenance-Based Intrusion Detection via Multi-Scale Graph Representation Learning.
.- SADGA: A Self Attention GAN-Based Adversarial DGA with High Anti-Detection Ability.
