Evaluating Data Anonymization Techniques for Privacy Preservation in Urban Mobility Data Analysis

1. Introduction 1.1 Background and Motivation 1.2 Research Objectives 1.3 Structure of the Thesis 2. Overview of Data Anonymization 2.1 Definition and Importance 2.2 Techniques and Methods 2.3 Challenges and Limitations 3. Urban Mobility Data Characteristics 3.1 Data Sources and Types 3.2 Privacy Concerns in Mobility Data 3.3 Data Sensitivity and Risk Assessment 4. Privacy Preservation Frameworks 4.1 Legal and Ethical Considerations 4.2 Anonymity vs Utility Balance 4.3 Threat Models in Urban Mobility 5. Evaluation of Anonymization Techniques 5.1 K-Anonymity and Its Extensions 5.2 Differential Privacy Application 5.3 Comparison of Technique Effectiveness 6. Case Studies and Data Analysis 6.1 Real-world Urban Data Sets 6.2 Methodology of Analysis 6.3 Results and Interpretation 7. Challenges in Practical Implementation 7.1 Scalability Issues 7.2 Real-time Data Processing Challenges 7.3 Adaptability to Diverse Environments 8. Conclusion and Future Work 8.1 Summary of Findings 8.2 Implications for Policy and Practice 8.3 Directions for Future Research