Disrupting Ransomware Actors on the Bitcoin Blockchain: A Graph Embedding Approach

Abstract

Ransomware attacks have become increasingly sophisticated, often using cryptocurrency payments to evade traditional financial tracking. This paper presents a graph embedding approach for disrupting ransomware actors on the Bitcoin blockchain. We develop an innovative system that analyzes blockchain transactions to identify and track ransomware-related activities.

Our research addresses the challenges of:

• Blockchain Analysis: Tracking cryptocurrency transactions for ransomware payments
• Graph Embedding: Representing complex transaction networks as embeddings
• Ransomware Detection: Identifying patterns associated with ransomware activities
• Actor Disruption: Strategies for disrupting ransomware operations

The system demonstrates effectiveness in identifying ransomware actors and provides tools for law enforcement and security researchers.

Key Contributions

1. Graph Embedding Framework: Novel approach for blockchain transaction analysis
2. Ransomware Detection: Identification of ransomware-related transaction patterns
3. Actor Tracking: Methods for tracking ransomware actors across the blockchain
4. Disruption Strategies: Practical approaches for disrupting ransomware operations

Research Impact

This work advances the field of blockchain security and provides practical tools for combating ransomware attacks through cryptocurrency analysis.