International Journal of Advanced Research in Computer and Communication Engineering

Abstract: An Intrusion Detection System (IDS) is a critical security mechanism designed to monitor network traffic and system activities to identify malicious actions or policy violations. With the rapid growth of interconnected systems and the increasing sophistication of cyberattacks, traditional security solutions such as firewalls are no longer sufficient on their own. This project focuses on the design and implementation of an effective intrusion detection system that enhances network security by identifying both known and unknown attacks in real time.

The proposed IDS analyzes incoming data packets and system behavior to detect abnormal patterns that may indicate unauthorized access, denial-of-service attacks, or data breaches. Machine learning techniques are employed to learn from historical data and classify activities as normal or malicious, thereby improving detection accuracy and reducing false alarms. The system continuously adapts to new attack patterns, making it suitable for dynamic network environments.

Keywords: Intrusion Detection System, Network Security, Cyber Attacks, Machine Learning, Anomaly Detection, Signature-Based Detection, Network Monitoring, Malicious Traffic, Threat Detection, Data Analysis

Downloads: | DOI: 10.17148/IJARCCE.2025.1412151