2 papers
cs.LG2025
Binary Anomaly Detection in Streaming IoT Traffic under Concept Drift
Rodrigo Matos Carnier, Laura Lahesoo, Kensuke Fukuda
With the growing volume of Internet of Things (IoT) network traffic, machine learning (ML)-based anomaly detection is more relevant than ever. Traditional batch learning models fac…
cs.CR2024
GothX: a generator of customizable, legitimate and malicious IoT network traffic
Manuel Poisson, Rodrigo Carnier, Kensuke Fukuda
In recent years, machine learning-based anomaly detection (AD) has become an important measure against security threats from Internet of Things (IoT) networks. Machine learning (ML…