Large Language Models in Wireless Application Design: In-Context Learning-enhanced Automatic Network Intrusion Detection

arXiv:2405.11002v1 Announce Type: cross
Abstract: Large language models (LLMs), especially generative pre-trained transformers (GPTs), have recently demonstrated outstanding ability in information comprehension and problem-solving. This has motivated many studies in applying LLMs to wireless communication networks. In this paper, we propose a pre-trained LLM-empowered framework to perform fully automatic network intrusion detection. Three in-context learning methods are designed and compared to enhance the performance of LLMs. With experiments on a real network intrusion detection dataset, in-context learning proves to be …

application arxiv automatic communication communication networks context cs.ai cs.cr cs.lg design detection empowered framework generative gpts information intrusion intrusion detection language language models large llm llms network network intrusion networks problem problem-solving studies transformers wireless