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--- |
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license: mit |
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datasets: |
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- Mireu-Lab/NSL-KDD |
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metrics: |
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- accuracy |
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- f1 |
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base_model: Qwen/Qwen2.5-0.5B |
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pipeline_tag: question-answering |
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tags: |
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- intrusion-detection |
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- cybersecurity |
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- llm |
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- qwen |
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- tabular-reasoning |
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--- |
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# PCF_ID: A Novel Prompt Cast Framework for Intrusion Detection |
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[](https://huggingface.co/PHZane/PCF_ID-0.5B) |
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[](https://www.python.org/) |
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[](https://opensource.org/licenses/MIT) |
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## 馃搶 Model Overview |
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**PCF_ID-0.5B** is a fine-tuned version of **Qwen2.5-0.5B**, adapted for network intrusion detection using the **Prompt Cast Framework (PCF-ID)**. By transforming structured tabular records into semantically rich **Question鈥揜easoning鈥揂nswer (Q-R-A)** prompts, PCF_ID enables large language models to effectively reason over cybersecurity data. |
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PCF_ID-0.5B significantly outperforms: |
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- Raw LLMs (e.g., vanilla Qwen2.5-0.5B), |
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- Traditional machine learning models (e.g., Random Forest, SVM), |
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- Advanced graph neural networks (GNNs). |
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## 馃捇 Code & Reproduction |
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The full framework, preprocessing pipeline, and evaluation scripts are available at: |
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馃敆 [https://github.com/Zaneph1/PCF_ID](https://github.com/Zaneph1/PCF_ID) |