AI FOR INTERACTIVE SECURITY-BY-DESIGN ASSISTANCE: AUTOMATIC VULNERABLE ASSET EXTRACTION AND INTEGRATION INTO A REQSECDES FRAMEWORK

1. Introduction 1.1 Background and Context 1.2 Problem Statement 1.3 Objectives of the Study 1.4 Research Questions 1.5 Structure of the Thesis 2. Literature Review 2.1 AI in Security-by-Design 2.2 Vulnerable Asset Extraction Techniques 2.3 REQSECDES Framework Overview 2.4 Integration Approaches in Security 2.5 Challenges and Opportunities 3. Methodology 3.1 Research Design 3.2 Data Collection Methods 3.3 Analytical Techniques 3.4 Validation of Methods 3.5 Ethical Considerations 4. Development of AI Models 4.1 Model Architecture Selection 4.2 Training Data Preparation 4.3 Implementation of AI Algorithms 4.4 Model Evaluation Metrics 4.5 Challenges in Model Development 5. Vulnerability Asset Extraction Process 5.1 Automatic Extraction Techniques 5.2 Data Sources and Collection 5.3 Processing Pipeline Design 5.4 Integration with AI Models 5.5 Evaluating the Extraction Process 6. Integration into the REQSECDES Framework 6.1 Framework Extension Strategies 6.2 Asset Integration Workflow 6.3 Testing Integration Efficiency 6.4 Case Study Implementation 6.5 Lessons Learned 7. Results and Discussion 7.1 Analysis of Results 7.2 Comparison with Existing Methods 7.3 Implications for Security-by-Design 7.4 Discussion of Research Questions 7.5 Limitations of the Study 8. Conclusion and Future Work 8.1 Summary of Findings 8.2 Contributions to the Field 8.3 Recommendations for Practice 8.4 Suggestions for Further Research 8.5 Final Thoughts

1. How can AI-driven methodologies be employed to enhance the extraction of vulnerable assets for integration within a REQSECDES framework to improve security-by-design practices? 2. What challenges and opportunities arise in the automatic extraction and integration of vulnerable assets into the REQSECDES framework, and how can these impact the efficiency and effectiveness of security-by-design processes?