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Introduction

In recent years, with the exponential growth of network traffic, the need for effective network traffic analysis and classification has become crucial for ensuring network security and optimization. Traditional methods of network traffic analysis and classification have limitations in terms of accuracy and efficiency. With the advancements in Artificial Intelligence (AI) technologies, AI-driven solutions have emerged as a promising approach to address these challenges.

This thesis explores the use of AI-driven techniques for network traffic analysis and classification. The integration of AI algorithms, such as machine learning and deep learning, offers the potential to improve the accuracy and efficiency of network traffic analysis, leading to better network security and performance.

Chapter 1: Introduction
1.1 Introduction
1.2 Background of study
1.3 Problem Statement
1.4 Objective of study
1.5 Limitation of study
1.6 Scope of study
1.7 Significance of study
1.8 Structure of the Thesis
1.9 Definition of terms

Chapter 2: Literature Review
2.1 Overview of network traffic analysis
2.2 Traditional methods of network traffic analysis
2.3 AI-driven techniques for network traffic analysis
2.4 Machine learning algorithms for network traffic classification
2.5 Deep learning algorithms for network traffic classification
2.6 Challenges in network traffic analysis using AI
2.7 Applications of AI in network security
2.8 Current trends in AI-driven network traffic analysis
2.9 Gaps in existing research
2.10 Summary of literature review

Chapter 3: Research Methodology
3.1 Research design
3.2 Data collection and preprocessing
3.3 Feature selection and extraction
3.4 AI model selection
3.5 Training and testing process
3.6 Evaluation metrics
3.7 Validation techniques
3.8 Ethical considerations
3.9 Limitations of research methodology

Chapter 4: Discussion of Findings
4.1 Analysis of experimental results
4.2 Comparison of AI-driven techniques
4.3 Interpretation of findings
4.4 Implications for network security
4.5 Recommendations for future research

Chapter 5: Conclusion and Summary
5.1 Summary of key findings
5.2 Contributions of the study
5.3 Implications for practice
5.4 Limitations of the study
5.5 Future research directions
5.6 Conclusion

Overall, this thesis aims to contribute to the existing body of knowledge on AI-driven network traffic analysis and classification, with the objective of enhancing network security and performance. By leveraging the power of AI technologies, organizations can improve their network monitoring capabilities and better defend against cyber threats.

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