Poster: Symmetrical Pruning for Lightweight Network Anomaly Detector

We propose the Autoencoding Binary Classifiers (ABC), a novel supervised anomaly detector based on the Autoencoder (AE). There are two main approaches in anomaly detection: supervised and unsupervised. The supervised approach accurately detects ...

Time-series Anomaly Detection has important applications, such as credit card fraud detection and machine fault detection. Anomaly detection based on the generative model generally detect samples with high reconstruction errors as anomalies. ...

Many anomaly detection methods are unsupervised e.g. they only utilize the non-anomalous data for model training. Data points that deviate from the majority of the pattern are deemed as anomalies. However, in many cases, anomaly labels are available ...