slowmist/automatic-tron-address-clustering
We use machine learning and graph algorithms to analyze the attributes of TRON addresses with the goal of assisting in the tracking of illicit funds.
This project helps cryptocurrency forensic investigators and security analysts track illicit funds by analyzing public TRON transaction histories. It takes raw TRON transaction data and outputs categorized TRON addresses (Hot wallet, Cold wallet, Common users), along with insights into their connections and influence. The primary users are blockchain security professionals and financial crime investigators.
No commits in the last 6 months.
Use this if you need to identify and categorize TRON blockchain addresses to trace suspicious activities or follow the flow of digital assets.
Not ideal if you are looking to analyze cryptocurrencies other than TRON, or if you require real-time, low-latency transaction monitoring.
Stars
12
Forks
10
Language
Python
License
Apache-2.0
Category
Last pushed
Nov 11, 2022
Commits (30d)
0
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