Semi-Supervised Learning for Anomaly Traffic Detection via Bidirectional Normalizing Flows

arXiv:2403.10550v1 Announce Type: cross
Abstract: With the rapid development of the Internet, various types of anomaly traffic are threatening network security. We consider the problem of anomaly network traffic detection and propose a three-stage anomaly detection framework using only normal traffic. Our framework can generate pseudo anomaly samples without prior knowledge of anomalies to achieve the detection of anomaly data. Firstly, we employ a reconstruction method to learn the deep representation of normal samples. Secondly, these representations are normalized to …

arxiv cs.ai cs.cr cs.lg detection semi traffic