This PoC will demonstrate the robustness of MonB5G for identifying, detecting and then mitigating the in-slice and cross-slice attacks. The objective is to assess the efficiency of MonB5G, in terms of response time, for detecting both in-slice and cross-slice attacks while preventing both false negative and false positive detections. Further, the PoC will demonstrate that even under significant numbers/ratios of misbehaving entities, distributed learning can be carried out in a robust way.