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AnoGLA: Enhanced Network Anomaly Detection by Ch Ghovanloo is a document available to read on EtoBox.
The paper presents AnoGLA, a novel approach for network anomaly detection that combines graph convolution networks (GCN) and long short-term memory networks (LSTM) with an attention mechanism to enhance detection accuracy. By modeling complex communication patterns in network traffic and utilizing graph-structured data, AnoGLA effectively identifies anomalies that traditional methods struggle to detect. Experimental results demonstrate that AnoGLA outperforms existing solutions on real-world datasets, addre
- Author
- Ch Ghovanloo
- Language
- EN