Network-Wide Traffic Anomaly Detection and Localization Based on Robust Multivariate Probabilistic Calibration Model

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static.hindawi.com/articles/mpe/volume-2015/923792/figures/923792.fig.009a.svgz" name="923792.fig.009a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>RMPCM</td></tr><tr class="fig-image" id="b"><td><object data="https://static.hindawi.com/articles/mpe/volume-2015/923792/figures/923792.fig.009b.svgz" name="923792.fig.009b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>PCA</td></tr><tr class="fig-image" id="c"><td><object data="https://static.hindawi.com/articles/mpe/volume-2015/923792/figures/923792.fig.009c.svgz" name="923792.fig.009c" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(c) </b>ANTIDOTE</td></tr></table>

<div>Comparison of three methods’ test results with medium poisoning.</div>

Mathematical Problems in Engineering

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Figure 9

Figure 9: Network-Wide Traffic Anomaly Detection and Localization Based on Robust Multivariate Probabilistic Calibration Model 