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The rapid evolution of beyond fifth-generation (B5G) and sixth-generation (6G) networks has significantly driven the growth of Internet of Things (IoT) applications. These applications are characterised by: a massive connectivity, high security level, trust, wireless coverage, also ultra-low latency, high throughput, and ultra-reliability, especially for real-time oriented sessions or sensor like cameras. While traditional protocols like MQTT and CoAP are inadequate for such types of applications, under certain conditions, the 3GPP standard Session Initiation Protocol (SIP) emerges as a promising solution. However, SIP faces various Distributed Denial of Service (DDoS) threats, as INVITE flooding attacks presenting a significant challenge. This work presents a GRU-based Intrusion Detection System (IDS) to detect SIP-INVITE flooding attacks. Leveraging recurrent neural networks, the IDS efficiently process sequential SIP …