Smart Detection of Cyber Threats: A Machine Learning Approach to Real-Time Network Traffic Analysis

Smart Detection of Cyber Threats: A Machine Learning Approach to Real-Time Network Traffic Analysis

Damisetty Venkata Said Revanth - Electronic and Communication Engineering, Amrita Vishwa Vidyapeetham

Gidugu Bhavana Sri Anantha Lakshmi- Electronic and Communication Engineering , Amrita Vishwa Vidyapeetham

Sankranti Srikar - Electrical And Electronics Engineering, Amrita Vishwa Vidyapeetham

Vinay Kamal D N - Computer Science And Engineering , Kalinga Institute Of Industrial Technology

Abstract

In today's digital age, cybersecurity has become a necessity as organizations increasingly rely on networks to transmit sensitive information. Protecting these networks from malicious attacks is critical, yet traditional rule-based intrusion detection systems (IDS) are insufficient for detecting new or sophisticated intrusions. These systems rely on predefined attack signatures, which limit their ability to recognize evolving threats. This project aims to overcome these limitations by utilizing machine learning to detect anomalies in network traffic. By analysing real-time network data, the proposed system identifies deviations from normal behaviour, allowing it to recognize both known and unknown cyber threats with a high level of accuracy. This approach enhances network security and provides an adaptable solution to modern cybersecurity challenges.