Challenges in Tracing Proxy Addresses by Mining Bitcoin Fraternize Service Transactions

Abstract

Bitcoin plays a major role in digital online transactions with decentralized scattered Peer-to-Peer systems. Cryptocurrency framework permits individuals to exchange with proxy addresses in Fraternize services. Nowadays, Bitcoin users have been increasing rapidly due to various Fraternize services. Due to this, some illicit activities were happening by creating unknown addresses. We surveyed machine learning algorithms like Decision Tree and Random Forest to classify illicit transactions in the Bitcoin network which helps to improve True Positive rate (TPR), and also reviewed various Fraternize services to identify proxy addresses and trace the ownership of Bitcoin transactions. Furthermore, examines the challenges of tracing the proxy addresses in the Bitcoin ecosystem after fund transaction. For further implementation, Bitcoin Transaction Datasets were acquired from Kaggle.