Leveraging LLMs for Network Security
A new paradigm for intelligent threat detection
This research introduces a novel architecture for network attack detection powered by large language models, combining LLMs' contextual understanding with security domain expertise.
- Proposes a comprehensive framework for LLM-based network security
- Demonstrates effective detection of common attack types including DDoS and malicious traffic
- Highlights LLMs' ability to understand network context and threat patterns
- Showcases practical implemention through case studies
This approach represents a significant shift for security professionals, offering more intelligent, adaptive threat detection systems that can evolve with emerging attack vectors and leverage the semantic understanding capabilities of modern LLMs.