The anonymity and de-anonymity of blockchain and Bitcoin have always been a hot topic in blockchain related research. Since Bitcoin was created by Nakamoto in 2009, it has, to some extent, deviated from its currency attribute as a trading medium but instead turned into an object for financial investment and operations. In this paper, the power-law distribution that the Bitcoin network obeys is given, while traditional de-anonymous methods such as clustering fail to satisfy it. Therefore, considering the profit-oriented characteristics of Bitcoin traders in such occasion, we put forward a deanonymous heuristic approach that recognizes and analyzes the behavioral patterns of financial High-Frequency Transactions(HFT), with real-time exchange rate of Bitcoin involved. Basing on the heuristic approach, finally we established the de-anonymous method that matches the activity information of the IP with the transaction records in blockchain. Experiments on IP matching method are applied to the actual data. It turns out that similar behavioral pattern between IP and transaction records are shown, which indicates the superiority of IP matching method.
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