NS
zimingttkx/Network-Security-Based-On-ML
基于机器学习的网络安全检测系统 | 集成Kitsune/LUCID算法 | 支持ML/DL/RL模型 | 99.58%攻击检测准确率 | 19913 QPS | Docker/K8s部署
157 30 +0/wk
GitHub
beginner-friendly cybersecurity fastapi machine-learning ml-project python scikit-learn threat-detection web-application xgboost
Trend
3
Star & Fork Trend (14 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
zimingttkx/Network-Security-Based-On-ML has +0 stars this period . 7-day velocity: 0.6%.
Deep analysis is being generated for this repository.
Signal-backed technical analysis will be available soon.
| Metric | Network-Security-Based-On-ML | tsk-tsk | -deprecated-NVIDIA-GPU-Tensor-Core-Accelerator-PyTorch-OpenCV | aws-neuron-samples |
|---|---|---|---|---|
| Stars | 157 | 157 | 157 | 158 |
| Forks | 30 | 16 | 23 | 48 |
| Weekly Growth | +0 | +0 | +0 | +0 |
| Language | Python | Rust | Jupyter Notebook | Jupyter Notebook |
| Sources | 1 | 1 | 1 | 1 |
| License | MIT | MIT | Apache-2.0 | NOASSERTION |
Capability Radar vs tsk-tsk
Network-Security-Based-On-ML
tsk-tsk
Maintenance Activity 100
Last code push 7 days ago.
Community Engagement 96
Fork-to-star ratio: 19.1%. Active community forking and contributing.
Issue Burden 70
Issue data not yet available.
Growth Momentum 30
No measurable growth in the current period (first-day cold start expected).
License Clarity 95
Licensed under MIT. Permissive — safe for commercial use.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.