GitHub / spk-22 / Flow-a-gorithm

Flow-a-gorithm is an algorithm-centric framework for detecting anomalies in network traffic through graph-based modeling and subgraph analysis. This project combines subgraph isomorphism, incremental detection algorithms, and a Graph Convolutional Network (GCN) to identify suspicious patterns in dynamic network flow data.

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Topics: anomaly-detection, fusion-classifier, gcn, gradio, ids, incremental-pattern-matching, network-analysis, pytorch-geometric, subgraph-isomorphism, ullmann-algorithm

• Files
• Readme
• Dependencies