• Developed a project focused on classifying Encrypted traffic into distinct categories. • Utilized network data to generate packet block images representing traffic patterns. • Employed Convolutional Neural Networks (CNN) to classify the traffic based on the generated images by the accuracy of 73%. • Gained hands-on experience with deep learning, network security, and image processing techniques. • Builds upon the research paper: ”A Deep Learning-Based Encrypted VPN Traffic Classification Method Using Packet Block Image”.