ML Threat Detection Model with Kubeflow Integration

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Prompt Content

Develop a machine learning model (e.g., using TensorFlow, PyTorch, or scikit-learn) capable of detecting various API threats, such as DDoS attacks (high request rates from suspicious IPs), API abuse (unusual sequence of calls), or unauthorized access attempts. Integrate this model into a Kubeflow pipeline for automated training, validation, and deployment using Kubeflow Serving. Ensure the pipeline can be easily updated and retrained.

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