Transaction graph based key node identification for blockchain regulation

Abstract

The inherent distributed and anonymity features of the blockchain system may cause illegal activities like improper content dissemination, illegal transactions, money laundering, etc., posing a severe threat to the blockchain. Due to the ultra-large scale of the public chain system, identifying key nodes in the transaction network is usually cost-intensive and time-consuming. In this paper, we propose a transaction graph-based scheme to identify key nodes in the public blockchain, where a multi-stage key node detection algorithm is proposed. Real Ethereum transaction data validates the performance of the proposed scheme. It is shown that with a data volume of millions of items, our multi-stage approach can effectively eliminate low-value information from the data and realize high-efficiency key node detection, with similar performance compared to traditional algorithms without filtering, and an extremely large improvement in algorithm execution time.