A deep support vector data description based on variational autoencoder (Deep SVDD-VAE) is proposed in this paper to solve this problem. In the proposed model, VAE is used to reconstruct the input instances, while a spherical discriminative boundary is learned with the latent representations ...
Experiments show that the VAE-SVDD model can detect ADS-B anomaly data which is generated by attacks such as random position deviation and constant position deviation. Moreover, compared with other machine learning methods, this model is not only more adaptable, but also has a lower FPR and ...
This method consists of two modules: a VAE reconstructor and SVDD anomaly detector. In the VAE reconstruction module, firstly, bi-directional long short-term memory (BiLSTM) is used to replace the traditional feedforward neural network in VAE to capture the time correlation of sequences; then,...