Comprehensive Evaluation and Optimization Techniques for Enhancing Rule-Based Network Intrusion Detection Systems

1. Introduction 1.1 Background and Motivation 1.2 Research Objectives 1.3 Structure of the Thesis 2. Network Intrusion Detection Systems 2.1 Overview of NIDS 2.2 Types of NIDS 2.3 Limitations of Current NIDS 3. Rule-Based Detection Techniques 3.1 Definition and Characteristics 3.2 Rule Matching Process 3.3 Strengths and Weaknesses 4. Evaluation Methods 4.1 Assessment Criteria 4.2 Benchmarking Datasets 4.3 Performance Metrics 5. Optimization Techniques 5.1 Rule Optimization Strategies 5.2 Algorithmic Improvement Methods 5.3 Machine Learning Integration 6. Case Studies and Applications 6.1 Real-World NIDS Implementations 6.2 Case Study: Specific Network Environment 6.3 Lessons Learned 7. Challenges and Future Directions 7.1 Current Challenges in NIDS 7.2 Emerging Threats 7.3 Future Research Opportunities 8. Conclusion 8.1 Summary of Findings 8.2 Implications for Practice 8.3 Final Thoughts and Recommendations