Enhancing Cyber Security in Wireless Sensor Networks using ChatTracer in Large Language Models (LLMs)

Wireless Sensor Networks (WSNs) are crucial to applications in smart cities, agriculture, and healthcare; however, their open architecture makes them highly vulnerable to cyberattacks. To address this vulnerability, we introduce ChatTracer, a novel security framework leveraging a lightweight Large Language Model (LLM). Fine-tuned on the WSN-BFSF dataset using Low-Rank Adaptation (LoRA), our efficient DeepSeek model analyzes network communication patterns through natural language processing. ChatTracer achieves up to 99% accuracy in real-time detection of major threats like Blackhole, Flooding, and Selective Forwarding, providing a powerful and scalable defense for resource-constrained WSNs.