1. Introduction
  1.1 Background and Motivation
  1.2 Objectives of the Project
2. Privacy Preservation and Data Anonymization
  2.1 Legal and Regulatory Frameworks
  2.2 Principles of Data De-identification
3. Anonymization Techniques for Structured Data
  3.1 Generalization and Suppression Methods
  3.2 K-anonymity and L-diversity Models
4. De-identification of Unstructured Data
  4.1 Text Redaction and Tokenization
  4.2 Differential Privacy and Perturbation Techniques
5. Utility and Information Loss Analysis
  5.1 Quantitative Measures of Anonymization
  5.2 Trade-offs between Privacy and Data Utility