6 citations · 11 across the 2 of their papers we have counts for
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cs.LG2020
SparseIDS: Learning Packet Sampling with Reinforcement Learning
Maximilian Bachl, Fares Meghdouri, Joachim Fabini +1
Recurrent Neural Networks (RNNs) have been shown to be valuable for constructing Intrusion Detection Systems (IDSs) for network data. They allow determining if a flow is malicious…
cs.LG2019
Explainability and Adversarial Robustness for RNNs
Alexander Hartl, Maximilian Bachl, Joachim Fabini +1
Recurrent Neural Networks (RNNs) yield attractive properties for constructing Intrusion Detection Systems (IDSs) for network data. With the rise of ubiquitous Machine Learning (ML)…