Recomposition vs. Prediction: A Novel Anomaly Detection for Discrete Events Based On Autoencoder
Lun-Pin Yuan,
Peng Liu,
Sencun Zhu
Abstract:One of the most challenging problems in the field of intrusion detection is anomaly detection for discrete event logs. While most earlier work focused on applying unsupervised learning upon engineered features, most recent work has started to resolve this challenge by applying deep learning methodology to abstraction of discrete event entries. Inspired by natural language processing, LSTM-based anomaly detection models were proposed. They try to predict upcoming events, and raise an anomaly alert when a predic… Show more
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