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Unfairness among best-effort flows is a serious problem on the Internet. In particular, UDP flows or unresponsive flows that do not obey the TCP flow control mechanism can consume a large share of the available bandwidth. High-rate flows seriously affect other flows, so it is important to identify them and limit their throughput by selectively dropping their packets. As link transmission capacity increases and the number of active flows increases, however, capturing all packet information becomes more difficult. In this paper, we propose a novel method of identifying high-rate flows by using sampled packets. The proposed method simply identifies flows from which Y packets are sampled without timeout. The identification principle is very simple and the implementation is easy. We derive the identification probability for flows with arbitrary flow rates and obtain an identification curve that clearly demonstrates the accuracy of identification. The characteristics of this method are determined by three parameters: the identification threshold Y, the timeout coefficient K, and the sampling interval N. To match the experimental identification probability to the theoretical one and to simplify the identification mechanism, we should set K to the maximum allowable value. Although increasing Y improves the identification accuracy, both the required memory size and the processing power grow as Y increases. Numerical evaluation using an actual packet trace demonstrated that the proposed method achieves very high identification accuracy with a much simpler mechanism than that of previously proposed methods.