Encrypted Network Traffic Anomaly Detection

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I need the following work done: • Network Traffic Anomaly Detection: Modify the existing code to handle encrypted network traffic, specifically by focusing on analyzing traffic metadata. The goal is to detect malicious traffic even when the payload is encrypted (e.g., TLS traffic). • Use metadata features like packet size, timing information, flow duration, and inter-arrival times, instead of relying solely on payload inspection. • Incorporate machine learning models such as Random Forests or Deep Learning to identify patterns based on these metadata features. • Implement time-series anomaly detection to handle encrypted traffic. • Focus on improving detection performance by enhancing detection accuracy, F1-Score, and reducing false positives. Deliverable Req...

Keyword: Machine Learning

Delivery Time: 3 days left days

Price: $138.0

Computer Security Machine Learning (ML) Network Administration Python