Anomaly detection is an essential task for different fields in the real world. The imbalanced data and lack of labels make the task challenging. Deep learning models based on autoencoder (AE) have been applied to address the above difficulties successfully. However, in these AE-based deep ...
Anomaly detectionVAESVDDAs a key technology of the new generation air traffic surveillance system, ADS-B (Automatic Dependent Surveillance-Broadcast) is vulnerable to cyber security challenges because it lacks data integrity and authentication mechanism. For detecting ADS-B data attacks accurately, an ...
In response to these problems, this paper proposes a novel hybrid method for KPI anomaly detection based on VAE and support vector data description (SVDD). This method consists of two modules: a VAE reconstructor and SVDD anomaly detector. In the VAE reconstruction module, firstly, bi-...