Explanation

System Architecture

The Food Security Sandbox follows a microservices architecture with four main components:

1. Frontend (React.js): User interface for data upload, model training, and collaboration
2. App Server (Flask): Main application server handling authentication and coordination
3. Farmer Server (Flask): Handles dataset management and privacy-preserving operations
4. Param Server (Flask): Manages model training and parameter aggregation

Privacy-Preserving Mechanisms

The system implements several privacy-preserving techniques:

1. Differential Privacy: Adds calibrated noise to data to prevent individual identification
2. PCA Transformation: Reduces data dimensionality while preserving important features
3. Membership Inference Attack Detection: Monitors and reports potential privacy breaches
4. Sandboxed Processing: Isolates data processing to prevent unauthorized access

Collaborative Learning Workflow

1. Data Preparation: Farmers upload datasets with metadata
2. Similarity Matching: System identifies farmers with similar data characteristics
3. Privacy Enhancement: Data is processed with differential privacy techniques
4. Model Training: Collaborative model training using federated learning principles
5. Risk Assessment: Privacy risks are analyzed and reported
6. Model Deployment: Trained models are stored in the repository for future use