LLMs and RAG enhance DDoS attack detection in SDN

Researchers have developed a new framework using Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) to detect and mitigate Carpet-Bombing DDoS attacks in Software-Defined Networking (SDN). This approach leverages traffic features, semantic embeddings, and LLM inference for real-time classification without traditional supervised training. Experiments showed high accuracy and stability, with the Gemma-4-31B-IT model configuration yielding the best detection results, demonstrating the integration's effectiveness for adaptive SDN security. AI

IMPACT Integrates LLMs into network security for advanced threat detection and mitigation.

RANK_REASON This is a research paper detailing a novel method for network security using LLMs and RAG. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

• Gemma-4-31B-IT
• Large Language Models
• Mohammed N. Swileh
• Retrieval-Augmented Generation
• Software-Defined Networking

• paper
• safety
• infra

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