Distributed network traffic anomaly refers to a traffic abnormal behavior involving many links of a network and caused bythe same source (e.g., DDoS attack, worm propagation). The anomaly transiting in a single link might be unnoticeable andhard to detect, while the anomalous aggregation from many links can be prevailing, and does more harm to the networks.Aiming at the similar features of distributed traffic anomaly on many links, this paper proposes a network-wide detectionmethod by performing anomalous correlation analysis of traffic signals' instantaneous parameters. In our method, traffic signals'instantaneous parameters are firstly computed, and their network-wide anomalous space is then extracted via traffic prediction.Finally, an anomaly is detected by a global correlation coefficient of anomalous space. Our evaluation using Abilene traffic tracesdemonstrates the excellent performance of this approach for distributed traffic anomaly detection.
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