Silvia Farraposo

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—The occurrence of a traffic anomaly is always responsible for a degradation of performance. The anomaly can be observable, at some scale, in different ways: an increase in the number of packets, an increase in the number of bytes, a concentration of packets around a port number, etc. In this paper we propose an anomaly independent methodology for detecting(More)
This paper deals with a new iterative Network Anomaly Detection Algorithm – NADA, which accomplishes the detection, classification and identification of traffic anomalies. NADA fully provides all information required limiting the extent of anomalies by locating them in time, by classifying them, and identifying their features as, for instance, the source(More)
—In this paper we present a methodology for detecting traffic anomalies. To accomplish that, and as a demarcation from similar works, we combine multi-scale and multi-criteria analysis with a tomography process analysis. With a complete knowledge of traffic anomalies, we intend to define anomalies signatures that could be used in a large range of scopes as(More)
Several recent traffic monitoring studies proved that traffic is highly variable (sometimes not stationary), and in any cases exhibiting many disruptions in its throughput, that of course are damageable for providing a stable QoS. If some of these disruptions can be legitimate variations of traffic (because a user suddenly generates a big flow or flash(More)
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