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cicids-lightgbm-gatekeeper – AI Model by transformer112 | AlphaNeural AI

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transformer112/
cicids-lightgbm-gatekeeper

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intrusion-detection

tabular-classification

binary-classification

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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

python

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