Скачать или смотреть Phishing Website Detection Using Machine Learning & Deep Learning| IEEE Project |All Academic Levels

Phishing Website Detection Using Machine Learning & Deep Learning | IEEE Project | CSE | ISE Academic Levels.

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📌 Project Title: Phishing Website Detection Using Machine Learning & Deep Learning
💻 Implementation Code: Python
🎨 Frontend: HTML, CSS, JavaScript and Flask Framework
🛠️ IDE Tool: Jupyter Notebook
💰 Project Cost: [check on our website]

📖 Project Abstract:
The goal of this project is to use advanced machine learning techniques to construct a robust system for phishing website identification. ANN models and SVM machine learning algorithms will be employed in the project to classify URL attributes that are utilised to identify possible phishing threats. The project, to be implemented in Python language using Jupyter notebook, will compare these two models in terms of accuracy, efficiency, and scalability for the most viable approach. The proposed system will require the preprocessing of the URL data to include relevant features to be fed into the ANN and SVM models for training and evaluation. The final results of the experiment and evaluation of the two models will serve to establish the most effective model for filtering out phishing websites with as minimal false positive detections and computational power as possible.

🚀 What You’ll Learn in This Project:
✅ Data collection & feature extraction from websites
✅ ML models like SVM for URL classification.
✅ Deep Learning models like ANN for URL classification.
✅ Web app development using Flask
✅ phishing detection system integration

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