Authors: Aakanksha Raghunath Chaudhari, Sharmistha Sujit Sarkar
Abstract: With the rapid growth of digital communication and online services, network security has become a primary concern for organizations and individuals. Traditional intrusion detection systems (IDS) rely heavily on predefined signatures, making them ineffective against zero-day attacks and unknown threats. To overcome these limitations, AI-based anomaly detection systems have emerged as a powerful approach for identifying unusual patterns in network traffic that may indicate malicious activity. This research introduces NetGuard, an intelligent system that leverages machine learning and deep learning techniques to detect anomalies in network traffic. The system provides real-time threat detection, reduces false alarms, and enhances network resilience against evolving cyber threats.
DOI: https://doi.org/10.5281/zenodo.17570618
