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Thesis Overview

Title: Development of a Real-Time Intrusion Detection System

Introduction

In today’s digital age, the security of computer networks is of utmost importance. With the increasing number of cyber attacks and security breaches, it has become imperative for organizations to have robust intrusion detection systems in place. Intrusion detection systems are software applications that monitor network or system activities for malicious activities or policy violations. The need for real-time intrusion detection systems has become essential to detect and respond to cyber threats promptly.

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

Chapter 2: Literature Review
2.1 Overview of Intrusion Detection Systems
2.2 Types of Intrusion Detection Systems
2.3 Real-Time Intrusion Detection Systems
2.4 Machine Learning Techniques in Intrusion Detection
2.5 Challenges in Real-Time Intrusion Detection
2.6 Existing Systems and Technologies
2.7 Evaluation Metrics for Intrusion Detection Systems
2.8 Recent Advancements in Intrusion Detection
2.9 Best Practices in Intrusion Detection
2.10 Gaps in Current Research

Chapter 3: System Design and Methodology
3.1 System Architecture
3.2 Data Collection and Preprocessing
3.3 Feature Selection and Extraction
3.4 Machine Learning Model Selection
3.5 Training and Testing of the Model
3.6 Threshold Setting for Intrusion Detection
3.7 Real-Time Monitoring and Alerting
3.8 System Evaluation
3.9 Performance Metrics
3.10 Ethical Considerations

Chapter 4: System Implementation
4.1 Development Environment
4.2 Data Collection Tools
4.3 Implementation of Machine Learning Algorithms
4.4 Integration with Existing Security Systems
4.5 Testing and Validation
4.6 System Performance Tuning
4.7 User Interface Design
4.8 Documentation and User Training

Chapter 5: Conclusion and Summary
5.1 Summary of Findings
5.2 Contributions to the Field
5.3 Recommendations for Future Research
5.4 Practical Implications
5.5 Conclusion

Overall, this thesis aims to contribute to the field of cybersecurity by developing a real-time intrusion detection system that can effectively detect and mitigate cyber threats. By incorporating machine learning techniques and utilizing real-time monitoring, this system can enhance the security posture of organizations and better protect their digital assets.

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