Network Data Processing for Machine Learning Applications

A systematic process of capturing, processing, and utilizing network data for machine learning applications. It begins with the use of Wireshark to capture packets, resulting in raw PCAP files. These files undergo a feature extraction process to refine and organize the data into a structured dataset. The refined network record dataset is then ready for various machine learning applications, enabling the development of models and algorithms that can analyze, interpret, and make predictions based on the network data.