ARCADE: Adversarially Regularized Convolutional Autoencoder for Network Anomaly Detection. (arXiv:2205.01432v1 [cs.LG])

As the number of heterogenous IP-connected devices and traffic volume
increase, so does the potential for security breaches. The undetected
exploitation of these breaches can bring severe cybersecurity and privacy
risks. In this paper, we present a practical unsupervised anomaly-based deep
learning detection system called ARCADE (Adversarially Regularized
Convolutional Autoencoder for unsupervised network anomaly DEtection). ARCADE
exploits the property of 1D Convolutional Neural Networks (CNNs) and Generative
Adversarial Networks (GAN) to automatically build a profile of the normal
traffic based …

anomaly detection detection lg network