Blockchain Threat Intelligence
AI-powered analysis to detect Ethereum wallet associations with threat actors.
Academic Research
IEEE PublicationThis system is based on a peer-reviewed deep learning framework for Ethereum wallet classification. The model achieves 98.99% accuracy using a dual-objective VAE that combines reconstruction and classification loss, capturing complex temporal patterns, cross-chain bridge interactions, and network-topology characteristics.
Network Topology
Analyzes deep transaction graphs with advanced behavioral indicators covering structural, temporal, value-flow, and service-specific patterns.
Advanced VAE Engine
Deep learning architecture with self-attention mechanisms and residual connections, trained on verified Ethereum datasets.