Overcoming challenges in deep inspect of vpn and proxy by deep learning

Abstract

The rapid growth of proxying and VPN techniques has presented formidable challenges for internet operators in classifying network traffic. These methods not only hinder effective traffic policing and resource restriction but also introduce complexities by allowing VPNs to masquerade under application protocols. Furthermore, the increasing popularity of applications like Voice over IP (VoIP) and peer-to-peer (P2P) technologies further exacerbates the difficulty in controlling and classifying such traffic. Conventional techniques like Server Name Indication (SNI) analysis are witnessing diminishing effectiveness over time. Network providers now face the critical task of acquiring detailed knowledge about the specific applications and protocols utilised by their customers, enabling them to accurately allocate resources and ensure robust traffic management in this challenging landscape.