Design and Implementation of a WAF for XSS and CSRF Detection using Rule-Based and ML Approaches

1. Introduction 1.1 Background and Motivation 1.2 Problem Statement 1.3 Objectives of the Study 1.4 Structure of the Thesis 2. Literature Review 2.1 Web Application Security Basics 2.2 Overview of WAF Technologies 2.3 XSS and CSRF Attacks 2.4 Rule-Based vs. Machine Learning Approaches 3. Methodology 3.1 Research Design 3.2 Data Collection Methods 3.3 Experimental Setup 3.4 Evaluation Criteria 4. Rule-Based Detection System 4.1 Rule Definition Process 4.2 XSS Detection Rules 4.3 CSRF Detection Rules 4.4 Advantages and Limitations 5. Machine Learning Approaches 5.1 Feature Selection for ML Models 5.2 Model Training and Validation 5.3 Comparison of ML Algorithms 5.4 Integration with WAF 6. Implementation 6.1 System Architecture 6.2 Development Environment 6.3 Integration with Existing Systems 6.4 Testing and Debugging 7. Results and Discussion 7.1 Detection Rate Analysis 7.2 Performance Evaluation 7.3 Comparative Analysis of Approaches 7.4 Discussion of Findings 8. Conclusion 8.1 Summary of Contributions 8.2 Implications for Practice 8.3 Limitations of the Study 8.4 Recommendations for Future Research