Network Anomaly Detection

This project uses machine learning techniques to detect anomalies in network traffic. By identifying unusual patterns, it helps in protecting networks against cyber threats, such as intrusions, malware, and unauthorized access.

Features

• Real-time detection of anomalies in network traffic.
• Identifies suspicious activities, including intrusions and unauthorized access.
• Provides actionable insights with anomaly alerts and risk scores.
• Integrates with existing network monitoring tools for enhanced security.

Installation

To set up the Network Anomaly Detection system on your local machine, follow these steps:

1. Clone the Repository

   git clone https://github.com/username/network-anomaly-detection.git
   cd network-anomaly-detection

2. Set Up Virtual Environment (Optional but Recommended)

   python3 -m venv venv
   source venv/bin/activate   # On Windows: venv\Scripts\activate

3. Install Required Packages

   pip install -r requirements.txt

Usage

To start detecting anomalies in your network traffic, run the main script:

python app.py

Monitor network data in real-time and receive alerts on suspicious activities.

Results

The system provides detailed reports on network anomalies, helping security teams to respond promptly to potential threats.