Block Number-Based Address Clustering for Bitcoin Taproot Upgrade - Gyeong Min Baek; Young Ah Shin; Gye Hyun Jang; Ik Rae Jeong (IEEE Access)
Bitcoin address clustering is a technique used for Bitcoin deanonymization to determine address ownership. It serves as a valuable method for assessing the level of anonymity within the system and detecting addresses associated with illicit activities. The recent Taproot soft fork in Bitcoin has introduced significant privacy enhancements, making deanonymization more challenging. In this paper, we propose a novel on-chain heuristic approach, block number-based address clustering, which leverages the fundamental principle of 6 block confirmations for double-spending prevention. By relying on the trust relationships between transacting parties, our method enables the generation of clusters even upon the soft fork, where existing methods encounter challenges. To evaluate our heuristics, we analyze our approach using the address reduction ratio and pure contribution as key metrics. The results show the effectiveness of our method both before and after the soft fork, which implies that our approach remains unaffected by the usage of Taproot transactions. Furthermore, we provide real-world empirical cases that validate the practicality of our heuristics. As shown in the investigation cases conducted by the Korean National Police Agency, our method can generate new clusters and improve address ownership identification compared to the previous approaches.