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XFinder: Detecting Unknown Anomalies in Distributed Machine Learning Scenario
2021
Frontiers in Computer Science
In recent years, the emergence of distributed machine learning has enabled deep learning models to ensure data security and privacy while training efficiently. Anomaly detection for network traffic in distributed machine learning scenarios is of great significance for network security. Although deep neural networks have made remarkable achievements in anomaly detection for network traffic, they mainly focus on closed sets, that is, assuming that all anomalies are known. However, in a real
doi:10.3389/fcomp.2021.710384
fatcat:gd27iynrznc3zohj5ihpyt255q