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.

Incremental unidirectional and bidirectional graph transformations with the Democles pattern matching engine

Flow-a-gorithm is a project designed to detect anomalies in network traffic using graph-based techniques. It processes data to identify potential security threats, offering a clear solution for network monitoring. 🛡️💻

Incremental unidirectional and bidirectional graph transformations with the HiPE incremental parallel pattern matching engine