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Introduction

In today’s fast-paced digital world, cyber threats are constantly evolving and becoming more sophisticated, posing a significant challenge to organizations’ network security. Traditional manual network security approaches are no longer sufficient to defend against the growing number of threats. As a result, there is a need for advanced technologies such as Artificial Intelligence (AI) to provide automated network security orchestration and automation.

AI-driven network security orchestration and automation leverage machine learning algorithms and AI capabilities to automate threat detection, response, and remediation processes. This thesis aims to explore the potential of AI-driven network security orchestration and automation in enhancing the overall network security posture of organizations.

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 Evolution of network security
2.2 AI in network security
2.3 Network security orchestration and automation
2.4 Benefits of AI-driven network security
2.5 Challenges of AI-driven network security
2.6 Case studies on AI-driven network security
2.7 Integration of AI with existing security solutions
2.8 Regulatory considerations in AI-driven network security
2.9 Future trends in AI-driven network security
2.10 Gaps in existing research on AI-driven network security

Chapter 3: Research Methodology

3.1 Research design
3.2 Data collection methods
3.3 Data analysis techniques
3.4 Sampling techniques
3.5 Ethical considerations
3.6 Research limitations
3.7 Research assumptions
3.8 Validation of findings

Chapter 4: Discussion of Findings

4.1 Analysis of research findings
4.2 Comparison of findings with existing literature
4.3 Implications of findings
4.4 Recommendations for future research
4.5 Practical implications for organizations
4.6 Limitations of the study
4.7 Conclusion

Chapter 5: Conclusion and Summary

5.1 Summary of key findings
5.2 Conclusions
5.3 Contributions to the field
5.4 Recommendations for practitioners
5.5 Recommendations for future research
5.6 Conclusion

Thesis Overview:

AI-driven network security orchestration and automation have emerged as a promising solution to address the challenges posed by modern cyber threats. This thesis will provide a comprehensive analysis of the role of AI in enhancing network security through automation and orchestration. The literature review will explore the evolution of network security, the benefits and challenges of AI-driven network security, and future trends in the field. The research methodology section will outline the design, data collection methods, and analysis techniques used in the study. The discussion of findings will present an in-depth analysis of the research findings, their implications, and recommendations for future research. Finally, the conclusion and summary chapter will summarize the key findings, conclusions, and contributions of the study to the field of AI-driven network security orchestration and automation.

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