Applying Autoencoder-Based GNNs for High-Throughput Network Anomaly Detection in NetFlow Data – NVIDIA Technical Blog News and tutorials for developers, data scientists, and IT admins 2025-07-03T22:20:47Z http://www.open-lab.net/blog/feed/ Dhruv Nandakumar <![CDATA[Applying Autoencoder-Based GNNs for High-Throughput Network Anomaly Detection in NetFlow Data]]> http://www.open-lab.net/blog/?p=99171 2025-05-29T19:05:12Z 2025-05-08T22:18:41Z As modern enterprise and cloud environments scale, the complexity and volume of network traffic increase dramatically. NetFlow is used to record metadata about...]]> As modern enterprise and cloud environments scale, the complexity and volume of network traffic increase dramatically. NetFlow is used to record metadata about...cybersecurity image

As modern enterprise and cloud environments scale, the complexity and volume of network traffic increase dramatically. NetFlow is used to record metadata about the traffic flows traversing a network device such as a router, switch, or host. NetFlow data, essential for understanding network traffic, can be effectively modeled as graphs where edges capture properties such as connection duration and��

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