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We used unsupervised machine learning to identify anomalous patterns of network traffic that suggest intrusion. Such techniques allow one to classify network traffic into clusters that emerge from the training data and do not require that signatures already be known. Data is from the National Collegiate Cybersecurity Defense Competition (NCCDC). All but the TCP connections were filtered out, and the...