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Multivariate Time Series characterization and forecasting of VoIP traffic in real mobile networks
Predicting the behavior of real-time traffic (e. g., VoIP) in mobility scenarios could help the operators to better plan their network infrastructures and to optimize the allocation of resources.
Supervised Feature Selection Techniques in Network Intrusion Detection: a Critical Review
Machine Learning (ML) techniques are becoming an invaluable support for network intrusion detection, especially in revealing anomalous flows, which often hide cyber-threats.
Experimental Review of Neural-based approaches for Network Intrusion Management
This leads to interesting guidelines for security managers and computer network practitioners who are looking at the incorporation of neural-based ML into IDS.
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