An Unsupervised Machine Learning-based Method for Detection and Explanation of Anomalies in Cloud Environments

To provide the users with ultra reliability, future 6G networks need to be equipped with fully automated anomaly detection systems. 6G is envisioned to be driven by machine learning capabilities to detect anomalies autonomously while dealing with multi-dimensional data with heterogeneous characteristics. In this paper, we propose our hybrid single-/multiple-threshold anomaly detection method, whic...