Learning at the edge : simulated DDoS detection in 5G networks
The growing use of 5G networks for critical services makes them vulnerable to Distributed Denial of Service (DDoS) attacks. While numerous Machine Learning (ML)-based approaches have been proposed, the real-world deployability of these models remains understudied. This work presents what is, based on existing literature, the first simulation-driven methodology to evaluate both the transferability
