Anika Schumann

An Anomaly Detection and Explainability Framework using Convolutional Autoencoders for Data Storage Systems

Anomaly detection in data storage systems is a challenging problem due to the high dimensional sequential data involved, and lack of labels. The state of the art for automating anomaly detection in these systems typically relies on hand crafted rules and thresholds which mainly allow to distinguish…