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Multi-stage Attack Detection and Prediction Using Graph Neural Networks: An IoT Feasibility Study
With the ever-increasing reliance on digital networks for various aspects of modern life, ensuring their security has become a critical challenge.
Efficient Network Representation for GNN-based Intrusion Detection
The last decades have seen a growth in the number of cyber-attacks with severe economic and privacy damages, which reveals the need for network intrusion detection approaches to assist in preventing cyber-attacks and reducing their risks.
Predicting Bandwidth Utilization on Network Links Using Machine Learning
Predicting the bandwidth utilization on network links can be extremely useful for detecting congestion in order to correct them before they occur.
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