St. Petersburg University of Aerospace Instrumentation. For system tasks we could form a rate of messages flows between nodes of different type’s matrix L. The value of element Lij of this matrix is ...

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In this paper, we propose a novel approach called the Partially-Supervised Graph Derivation Network with Meta Learning (PS-GDNML) for time series anomaly detection. PS-GDNML combines the power of ...

We propose GTAE-IDS, a novel unsupervised packet-based graph neural network framework aimed at early and precise anomaly detection in network traffic. GTAE-IDS employs graph embeddings to capture and ...