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The system works by analyzing network data to identify potential security threats. It features an easy-to-use web interface that lets users monitor these threats in real-time and receive immediate alerts if any suspicious activity is detected. This combination of advanced technology and user-friendly design helps keep networks secure and allows for quick responses to potential security issues.\n\n\u003c/p\u003e\n\u003c/div\u003e\n\n## Features\n\u003cdiv style=\"background-color: #d4edda; padding: 15px; border-radius: 10px;\"\u003e\n  \u003ch3 style=\"color: #155724;\"\u003e✨ Key Features\u003c/h3\u003e\n  \u003cul\u003e\n    \u003cli\u003e🔒 \u003cstrong\u003eIntrusion Detection:\u003c/strong\u003e CNN-based system to detect unauthorized access attempts.\u003c/li\u003e\n    \u003cli\u003e🌐 \u003cstrong\u003eWeb Interface:\u003c/strong\u003e Responsive interface using HTML, CSS, and Flask.\u003c/li\u003e\n    \u003cli\u003e📊 \u003cstrong\u003eReal-time Monitoring:\u003c/strong\u003e Real-time alerts and monitoring capabilities.\u003c/li\u003e\n  \u003c/ul\u003e\n\u003c/div\u003e\n\n## Technologies\n\u003cdiv style=\"background-color: #cce5ff; padding: 15px; border-radius: 10px;\"\u003e\n  \u003ch3 style=\"color: #004085;\"\u003e🛠️ Technologies Used\u003c/h3\u003e\n  \u003cul\u003e\n    \u003cli\u003ePython\u003c/li\u003e\n    \u003cli\u003eHTML\u003c/li\u003e\n    \u003cli\u003eCSS\u003c/li\u003e\n    \u003cli\u003eFlask\u003c/li\u003e\n    \u003cli\u003eDatasets\u003c/li\u003e\n    \u003cli\u003eConvolutional Neural Networks (CNN)\u003c/li\u003e\n  \u003c/ul\u003e\n\u003c/div\u003e\n\n## Installation\n```bash\n# Clone the repository\ngit clone https://github.com/badhanhitesh/SecureCNN.git\n\n# Navigate to the project directory\ncd SecureCNN\n\n# Install dependencies\npip install -r requirements.txt\n\n# Run the application\npython app.py\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbadhanhitesh%2Fintrusion-detection","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbadhanhitesh%2Fintrusion-detection","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbadhanhitesh%2Fintrusion-detection/lists"}