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Lecture Notes in Computer Science
Being able to timely detect new kinds of attacks in highly distributed, heterogeneous and evolving networks without generating too many false alarms is especially challenging. Many researchers proposed various anomaly detection techniques to identify events that are inconsistent with past observations. While supervised learning is often used to that end, security experts generally do not have labeled datasets and labeling their data would be excessively expensive. Unsupervised learning, thatdoi:10.1007/978-3-030-52683-2_12 fatcat:qn52lph33jez5j6uneiztzibnm