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This paper investigates the potential contributions of traffic flow measurements in monitoring and network diagnostics. The basic idea is that information of diagnostic relevance may be obtained from the detection of local anomalies in a traffic trace. For this purpose, this paper introduces a novel approach in the analysis of aggregate traffic, based on the determination of empirical rate-interval curves (RICs). These curves allow an analysis of flow quantiles versus time scale, which is helpful both in the investigation of the scaling properties of network traffic and in diagnostics. RIC-based analyses of traffic measurements taken from different networks are presented and show that the proposed approach appears to be effective in evidencing potential flow anomalies.