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Despite the rapid advance in networking technologies, detection of network anomalies at high-speed switches/routers is still far from maturity. To push the frontier, two major technologies need to be addressed. The first one is efficient feature-extraction algorithms/hardware that can match a line rate in the order of Gb/s; the second one is fast and effective anomaly detection schemes. In this paper, the authors focus on design of efficient data structure and algorithms for feature extraction. Specifically, they propose a novel data structure that extracts so called Two-Directional (2D) matching features, which are shown to be effective indicators of network anomalies.
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