Intellectual Property India Publishes Patent Application for Ai Based Cyber Threat Detection System Using Machine Learning For Real Time Network Security Monitoring And Intelligent Attack Prevention

MUMBAI, India, July 13 -- Intellectual Property India has published a patent application (202641064564 A) filed by Nandha Engineering College on May 22, 2026, for Ai Based Cyber Threat Detection System Using Machine Learning For Real Time Network Security Monitoring And Intelligent Attack Prevention.

Inventors include Dr. S. Devi; and R. Sowmini.

The application for the patent was published on July 10, 2026, under issue no. 28/2026.

Abstract: The rapid growth of digital technologies and internet usage has significantly increased the risk of cyber threats, making network security a critical concern for organizations and individuals. Traditional security mechanisms often fail to detect sophisticated and evolving cyber-attacks in real time. To address this challenge, this project proposes an AI-Based Cyber Threat Detection System using Machine Learning for real-time network security monitoring and intelligent attack pre vent ion. The system leverages advanced machine learning algorithms such as Decision Trees, Random Forest, and Support Vector Machines (SVM) to analyze network traffic data and identify potential threats. By training the model on labeled datasets containing both normal and malicious activities, the system can accurately classify and detect various types of cyber-attacks, including intrusion attempts, malware activities, and unauthorized access. The proposed system operates in real time, continuously monitoring incoming and outgoing network packets. It extracts relevant features from the data, processes them through trained models, and generates alerts when suspicious behavior is detected. This proactive approach helps in minimizing damage, reducing response time, and enhancing overall network security. Additionally, the system is designed to be scalable and adaptive, allowing it to learn from new attack patterns and improve detection accuracy over time. The integration of artificial intelligence ensures efficient handling of large volumes of data and reduces dependency on manual monitoring.Overall, this project provides a robust, intelligent, and automated solution for modem cybersecurity challenges, improving threat detection capabilities and ensuring safer digital environments.

Disclaimer: Curated by HT Syndication.