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cicids-lightgbm-gatekeeper
transformer112/cicids-lightgbm-gatekeeper
cicids-lightgbm-gatekeeper is a tabular classification model from transformer112. Use it for the tabular classification task on the model card, and read the license before you ship it in a product. It is set up for lightgbm. The card lists the license as mit.
Binary classifier for the Hybrid Edge-to-Core IDS. Acts as a fast filter to distinguish benign from malicious network flows.
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Public
Updated Jun 17, 2026
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.txt2.7 MB · 100%
At a glance
- Task
- Tabular Classification
- Library
- lightgbm
- License
- mit
- Access
- Public
- Created
- Jun 17, 2026
- Updated
- Jun 17, 2026
- SHA
- cb4c883d
Model card
From the Hugging Face model README
CICIDS LightGBM Gatekeeper (Stage 1)
Binary classifier for the Hybrid Edge-to-Core IDS. Acts as a fast filter to distinguish benign from malicious network flows.
Performance
- Accuracy: 99.87%
- Precision: 99.69%
- Recall: 99.89%
- Macro F1: 99.85%
- Optimal Threshold: 0.4837
Architecture
- Type: Gradient Boosted Decision Trees
- Estimators: 250
- Tuning: Optuna (10 trials)
- Input: 58 numerical flow features
Usage
import lightgbm as lgb
model = lgb.Booster(model_file='stage1_gatekeeper.txt')
prob = model.predict(features.reshape(1, -1))[0]
is_attack = prob >= 0.4837
- Task
- Tabular Classification
- Library
- lightgbm
- License
- mit
- Created
- Jun 17, 2026
- Updated
- Jun 17, 2026