VoIP Traffic Detection in Tunneled and Anonymous Networks Using Deep Learning

Network management is facing a great challenge to analyze and identify encrypted network traffic with specific applications protocols. A significant number of users applying different encryption techniques services hide the true nature communication. These challenges attract community improve security enhance service quality. managers need novel cope failure shortcomings port-based payload-based classification methods due emergent technologies. Mainly, famous hopping mechanisms used make unknown anonymous are VPN (virtual private network) TOR (Onion Router). This paper presents scheme unveil easily tunneled traffic. The proposed identification uses highly desirable deep learning efficiently extract Voice over IP (VoIP) Non VoIP ones within flows. Finally, captured has been classified into four categories, i-e., VoIP, Non-VoIP, Non-VoIP. experimental results show that our engine extremely robust