Securing ML Pipelines: From Data to Deployment

Securing the ML Lifecycle

Each stage of the ML pipeline presents security risks that must be addressed systematically.

Pipeline Stages

Data Collection

Data Storage

Training

Model Storage

Deployment

Inference

Threat Vectors

Data Stage

Training Stage

Deployment Stage

Security Controls

Technical

Process

Organizational

Best Practices

Tools

Conclusion

Comprehensive security across the ML pipeline is essential for trustworthy AI systems.