Authors : A. Pallavi; Jennifer Mary S.; Dr. Girish Kumar D.

Volume/Issue : Volume 11 - 2026, Issue 4 - April

Google Scholar : https://tinyurl.com/58eadw89

Scribd : https://tinyurl.com/2uu7reyt

DOI : https://doi.org/10.38124/ijisrt/26apr2461

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : The increasing use of network-based systems has the increase in cyber threats—such as malware, denial-of-service attacks, and unauthorized access—has made it clear that traditional security approaches often struggle to identify these risks in real time. This project proposes an Intelligent Adaptive Cyber Threat Detection System that analyses Network traffic optimization through adaptive data systems to automatically identify and classify malicious activities. Developed using Python and the Flask framework, the system allows users to upload network data in CSV format through a web dashboard, where it is processed and analysed to detect potential threats. The detected results are stored in a MySQL database and visualized through an interactive dashboard that displays alerts, statistics, and detection accuracy. The system offers a scalable, user-friendly, and efficient solution for real-time cyber threat monitoring and improved network security.

Keywords : Cyber Security, an Intelligent Security System Designed for Real-Time Monitoring Incorporates Threat Detection, Network Traffic Evaluation, and Anomaly Identification, Using the Python Flask Framework for Development, CSV-Based Data Handling, a MySQL Database for Storage, and a Web-Based Dashboard for Visualization.

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