29 citations · 75 across the 10 of their papers we have counts for
4 papers · 1 filter
Detecting Fair Queuing for Better Congestion Control
Maximilian Bachl, Joachim Fabini, Tanja Zseby
Low delay is an explicit requirement for applications such as cloud gaming and video conferencing. Delay-based congestion control can achieve the same throughput but significantly…
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…
LFQ: Online Learning of Per-flow Queuing Policies using Deep Reinforcement Learning
Maximilian Bachl, Joachim Fabini, Tanja Zseby
The increasing number of different, incompatible congestion control algorithms has led to an increased deployment of fair queuing. Fair queuing isolates each network flow and can t…
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…