1. Introduction
  - Background and Rationale
  - Objectives of the Project
2. Literature Review
  - Recommendation Systems and Privacy Concerns
  - Privacy-Preserving Technologies
  - State-of-the-Art Approaches
3. System Architecture and Design
  - User Data Collection and Anonymization
  - Privacy-Preserving Recommendation Algorithms
  - Federated Learning Framework
4. Implementation Details
  - Differential Privacy Integration
  - Federated Learning Model Implementation
  - User Interface Design
5. Privacy and Security Analysis
  - Privacy Threat Model
  - Privacy-Preserving Measures
  - Security Considerations