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Anomaly traffic often breaks out without any omen and brings a breakdown to networks in a short time, and thus the adaptive detection of anomalies in network traffic is an important and challenging task. In this paper, we propose a wavelet-based adaptive approach to detect anomalies in network traffic. We can use wavelet packet transform and continuous wavelet transform to perform the adaptive detect anomaly. First, wavelet packet transform is exploited to extract the anomaly characteristics on the different scales. Then continue wavelet transform is exploited to obtain the further anomaly information about network traffic. Simulation results show that our method is effective and feasible.