3 papers
cs.LG2024
SDOoop: Capturing Periodical Patterns and Out-of-phase Anomalies in Streaming Data Analysis
Alexander Hartl, Félix Iglesias Vázquez, Tanja Zseby
Streaming data analysis is increasingly required in applications, e.g., IoT, cybersecurity, robotics, mechatronics or cyber-physical systems. Despite its relevance, it is still an…
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)…
cs.CR2019
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…