Anomaly Detection in Network Traffic Using Advanced Machine Learning Technique | Python IEEE Project

Описание: Anomaly Detection in Network Traffic Using Advanced Machine Learning Techniques | Python IEEE Final Year Project 2025 - 2026.
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🔗Email: [email protected],
🌐Website: https://www.jpinfotech.org

🚀IEEE Base Paper Title: Anomaly Detection in Network Traffic Using Advanced Machine Learning Techniques.
📌Our Proposed Project Title: Machine Learning based Intrusion Detection System for Detecting Various Attacks
💡Implementation: Python.
🔬Algorithm / Model Used: CatBoost Classifier, ExtraTree Classifier, Gradient Boosting Classifier.
🌐Web Framework: Flask.
🖥️Frontend: HTML, CSS, JavaScript.
💰Cost (In Indian Rupees): Rs.5000/

📘Project Abstract:
The exponential growth of internet usage has heightened the need for robust cybersecurity mechanisms to detect and prevent malicious activities in network traffic. This project, titled "Anomaly Detection in Network Traffic Using Advanced Machine Learning Techniques," focuses on developing a Intrusion Detection System (IDS) that leverages powerful machine learning models to identify and classify various types of cyber-attacks. Built using Python as the core programming language, with HTML, CSS, and JavaScript for the front-end and Flask as the web framework, the system provides an interactive platform for real-time anomaly detection.

📍REFERENCE:
STEPHANIE NESS, VISHWANATH ESWARAKRISHNAN, HARISH SRIDHARAN, VARUN SHINDE, NAGA VENKATA PRASAD JANAPAREDDY, AND VINEET DHANAWAT, “Anomaly Detection in Network Traffic Using Advanced Machine Learning Techniques”, IEEE ACCESS, VOLUME 13, 2025.

🏷️tags:
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