This paper aims to address the problem of anomaly detection and discrimination in complex behaviours, where anomalies are subtle and difficult to detect owing to the complex tempo...
This paper presents a novel approach of applying both positive selection and negative selection to supervised learning for anomaly detection. It first learns the patterns of the n...
DADICC is the abbreviated name for an intelligent system able to detect on-line and diagnose anomalies as soon as possible in the dynamic evolution of the behaviour of a power pla...
— High-speed backbones are regularly affected by various kinds of network anomalies, ranging from malicious attacks to harmless large data transfers. Different types of anomalies...
Evaluating anomaly detectors is a crucial task in traffic monitoring made particularly difficult due to the lack of ground truth. The goal of the present article is to assist rese...
Romain Fontugne, Pierre Borgnat, Patrice Abry, Ken...