AI-Based Intrusion Detection System for Network Security

Cyberattacks are becoming increasingly sophisticated, making traditional security mechanisms insufficient. This research project proposes an AI-based intrusion detection system to enhance network security.

Problem Statement

Signature-based detection systems struggle to identify novel and evolving cyber threats.

Research Objectives

The objective is to detect anomalous network behavior using machine learning models.

Methodology

Network traffic data is collected and analyzed. Anomaly detection algorithms classify traffic as normal or suspicious.

Technologies Used

Machine learning frameworks, network monitoring tools, and cybersecurity datasets are used.

Expected Outcomes

The system improves threat detection accuracy and reduces response time.

Conclusion

This project demonstrates the application of AI in strengthening digital security infrastructures.