29 citations · 75 across the 10 of their papers we have counts for
4 papers · 1 filter
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)…
Cocoa: Congestion Control Aware Queuing
Maximilian Bachl, Joachim Fabini, Tanja Zseby
Recent model-based congestion control algorithms such as BBR use repeated measurements at the endpoint to build a model of the network connection and use it to achieve optimal thro…
Walling up Backdoors in Intrusion Detection Systems
Maximilian Bachl, Alexander Hartl, Joachim Fabini +1
Interest in poisoning attacks and backdoors recently resurfaced for Deep Learning (DL) applications. Several successful defense mechanisms have been recently proposed for Convoluti…
City-GAN: Learning architectural styles using a custom Conditional GAN architecture
Maximilian Bachl, Daniel C. Ferreira
Generative Adversarial Networks (GANs) are a well-known technique that is trained on samples (e.g. pictures of fruits) and which after training is able to generate realistic new sa…