The Unique Dressing of Transactions: Wasabi CoinJoin Transaction Detection

As Bitcoin’s blockchain allows third-party entities to track and analyse the transaction activity of Bitcoin users, external Privacy-Enhancing Technology services are created to satisfy the user demand for transaction privacy. These services are predominantly utilised as instruments in illegal activities. In this paper, we investigate one of the most prominent Privacy-Enhancing Technology services, Wasabi Wallet and its CoinJoin mixing function. We obtained Wasabi CoinJoin transactions for different time periods via published sources to observe the transaction patterns and changes in the obscuring mechanism. We propose a detection method derived from the discovered sets of transaction patterns. The results of our experiment show that the Wasabi Wallet has not substantially changed its CoinJoin mixing mechanism since the start of its operation and the majority of the Wasabi CoinJoin transactions are identifiable with significantly high precision. We also test the application of our detection method on several well-known cryptocurrency theft incidents and discover instances where the stolen Bitcoins directly reach the detected Wasabi CoinJoin Transactions.