AI-based coresets is a powerful technique which enables the use of smaller sets of data instead of larger ones without compromising the quality of the output. This approach is based on highly efficient set of algorithms that reduce the data input on one hand, and execute anomaly detection routines on the reduced dataset (coreset), on the other hand. This technology has been applied to fixed big datasets, distributed data or to streaming data, which is highly relevant feature when we aim at network traffic anomaly detection.
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