SCNN-Attack: A Side-Channel Attack to Identify YouTube Videos in a VPN and Non-VPN Network Traffic

Encryption Protocols e.g., HTTPS is utilized to secure the traffic between servers and clients for YouTube other video streaming services, further communication, VPNs are used. However, these protocols not sufficient hide identity of videos from someone who can sniff network traffic. The present work explores methodologies features identify in a VPN non-VPN To such videos, side-channel attack using Sequential Convolution Neural Network proposed. results demonstrate that sequence bytes per second even one-minute sniffing predict with high accuracy. accuracy increased 90% non-VPN, 66% VPN, 77% mixed traffic, models two-minute sniffing.