5 papers · 1 filter
FlexFringe: Modeling Software Behavior by Learning Probabilistic Automata
Sicco Verwer, Christian Hammerschmidt
We present the efficient implementations of probabilistic deterministic finite automaton learning methods available in FlexFringe. These implement well-known strategies for state-m…
Optimal or Greedy Decision Trees? Revisiting their Objectives, Tuning, and Performance
Jacobus G. M. van der Linden, Daniël Vos, Daniël Vos +4
Recently there has been a surge of interest in optimal decision tree (ODT) methods that globally optimize accuracy directly, in contrast to traditional approaches that locally opti…
State Frequency Estimation for Anomaly Detection
Clinton Cao, Agathe Blaise, Annibale Panichella +1
Many works have studied the efficacy of state machines for detecting anomalies within NetFlows. These works typically learn a model from unlabeled data and compute anomaly scores f…
ENCODE: Encoding NetFlows for Network Anomaly Detection
Clinton Cao, Annibale Panichella, Sicco Verwer +2
NetFlow data is a popular network log format used by many network analysts and researchers. The advantages of using NetFlow over deep packet inspection are that it is easier to col…
Optimizing Interpretable Decision Tree Policies for Reinforcement Learning
Daniël Vos, Sicco Verwer
Reinforcement learning techniques leveraging deep learning have made tremendous progress in recent years. However, the complexity of neural networks prevents practitioners from und…