2 papers
cs.LG2020
EagerNet: Early Predictions of Neural Networks for Computationally Efficient Intrusion Detection
Fares Meghdouri, Maximilian Bachl, Tanja Zseby
Fully Connected Neural Networks (FCNNs) have been the core of most state-of-the-art Machine Learning (ML) applications in recent years and also have been widely used for Intrusion…
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…