A GEOMETRIC FRAMEWORK FOR UNSUPERVISED ANOMALY DETECTION: DETECTING INTRUSIONS IN UNLABELED DATA

作者: E Eskin , Andrew Arnold , Michael Prerau , Leonid Portnoy , Sal Stolfo

DOI: 10.7916/D8D50TQT

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摘要: … This training data is typically expensive to produce. We present a new geometric … for unsupervised anomaly detection, which are algorithms that are designed to process unlabeled data. …

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