Objective:

• Conduct research and development on AWS S3 storage for handling evidence data.
• Implement a solution to store evidence in S3 and log the operation using Consent Logger.

Tasks and Deliverables:

1. Research AWS S3 for Evidence Storage

• Understand S3 bucket setup, access policies, and security configurations.
• Explore encryption, versioning, and lifecycle management for stored evidence.
• Identify the best SDK/library (e.g., Boto3 for Python, AWS).

2. Implement Evidence Insertion into S3

• Write a function to upload evidence (files, JSON, or logs) to an S3 bucket.
• Ensure metadata tagging and structured folder organization (e.g., per user or case ID).
• Handle error management and retry mechanisms for robust storage operations.

3. Integrate Consent Logger for Logging

• Ensure each evidence upload is logged via the Consent Logger.
• Log details like timestamp, user ID, action performed, and S3 object reference.
• Store logs in a structured format for easy retrieval and auditing.

summary: -

✅ Perform R&D on AWS S3 storage best practices.
✅ Implement evidence insertion & logging using Consent Logger.
✅ Test the implementation with different file types and sizes.
✅ Optimize for security, performance, and error handling.