AnonXpose is a powerful tool designed to analyze and de-anonymize cryptocurrency transactions, focusing on dark web activities. The project leverages blockchain analysis and machine learning to track major dark web sites and identify entities operating within the dark web.
- Multi-layer Tracking Model: Analyzes both dark web and blockchain data for comprehensive tracking.
- Address Matching Algorithm: Identifies and traces cryptocurrency addresses.
- Multilayer Clustering Algorithm: Clusters Bitcoin transactions to identify patterns.
- Machine Learning Integration: Utilizes ML algorithms for analyzing interactions and mapping identities using techniques like CEX, ENS, and NFTs.
- Visualization Dashboard: Provides insights through a user-friendly interface for tracking and understanding transaction flows.
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Blockchain Analysis:
- Ethereum (ETH)
- Bitcoin (BTC)
- Monero (XMR)
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Machine Learning:
- Address Matching
- Clustering Algorithms
- Identity Mapping
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Frontend:
- HTML
- CSS
- JavaScript
- Vite
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Backend:
- Node.js
- Python (for ML models)
To set up the project locally, follow these steps:
- Clone the Repository:
git clone https://github.com/yourusername/anonxpose.git