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Subsequently, we also describe an anomaly detection method to detect the proposed attack.
Based on this model, an anomaly detection algorithm can detect out of profile behaviour, i.e., outliers.
We detect an anomaly only if both scan are coherent on the anomaly detection output.
Specialized Network Anomaly Detection.
Received signal strength anomaly detection.
Community-based Anomaly Detection System.
Figure 4 Content Anomaly Detection.
Currently, anomaly detection methods include anomaly detection based on classification, anomaly detection based on the nearest neighbor method, anomaly detection based on clustering, statistical anomaly detection, anomaly detection based on information theory, spectral theory anomaly detection, and so on [1].
Content anomaly detection, or point anomaly detection, has been well explored in literature.
The supervised anomaly detection approaches require the labeled dataset so as to establish anomaly detection models.
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The performance of the PLS-based KLD anomaly-detection methods is illustrated and compared to that of conventional PLS-based anomaly detection methods.
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