Diana Spears

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A novel approach is presented that bridges the gap between anomaly and misuse detection for identifying cyber attacks. The approach consists of an ensemble of classifiers that, together, produce a more informative output regarding the class of attack than any of the classifiers alone. Each classifier classifies based on a limited subset of possible features(More)
We examine the plausibility of using an Artificial Neural Network (ANN) and an Importance-Aided Neural Network (IANN) for the refinement of the structural model used to create full-wave tomography images. Specifically, we apply the machine learning techniques to classifying segments of observed data wave seismograms and synthetic data wave seismograms as(More)
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