FATE: Fuzzing for Adversarial examples in Tree Ensembles

Machine learning models are increasing in popularity and are nowadays used in a wide range of critical applications in fields such as Automotive, Aviation and Medical. Among machine learning models, tree ensemble models are a popular choice due to their competitive performance and high degree of explainability. Like most machine learning models...

Adversarial Traffic Modifications for the Network Intrusion Detection Domain: A Practical Adversarial Network Traffic Crafting Approach

Adversarial attacks pose a risk to machine learning (ML)-based network intrusion detection systems (NIDS). In this manner, it is of great significance to explore to what degree these methods can be viably utilized by potential adversaries. The majority of adversarial techniques are designed for unconstrained domains such as the image recognition...