A dataset from the UCI Machine Learning Repository containing information on Bitcoin addresses associated with ransomware activity. It is used for network analysis and security research, focusing on illicit transactions within the cryptocurrency ecosystem.
Use Cases
- Classify addresses as ransomware-related based on transaction features like total received amount and number of transactions.
- Analyze temporal patterns of ransomware payments using timestamps from transaction data.
- Identify network clusters of illicit addresses using graph features derived from Bitcoin transaction flows.
- Train anomaly detection models to flag suspicious address behavior using features like average transaction value.
Strengths
- Sourced from the authoritative UCI Machine Learning Repository.
- Focuses on a specific, high-impact security threat (ransomware).
Limitations
- Unknown number of rows and columns limits assessment of statistical power.
- Data freshness and temporal coverage are unknown, potentially making models stale.
Provenance
- Source
- UCI Machine Learning Repository
- Collection Method
- null
- Time Range
- null
- Freshness
- null
- Geography
- null