As the majority of Internet traffic is encrypted by the Transport Layer Security (TLS) protocol,
recent advances leverage Deep Learning (DL) models to conduct encrypted traffic …

Nowadays, encryption technology has been widely used to protect user privacy. With the
explosive growth of mobile Internet, encrypted TLS traffic rises sharply and occupies a great …

Traffic classification is essential in network management for a wide range of operations.
Recently, it has become increasingly challenging with the widespread adoption of …

Traffic classification is essential in network management for operations ranging from
capacity planning, performance monitoring, volumetry, and resource provisioning, to …

Traffic classification is essential for cybersecurity maintenance and network management,
and has been widely used in QoS (Quality of Service) guarantees, intrusion detection, and …

Encrypted traffic classification requires discriminative and robust traffic representation
captured from content-invisible and imbalanced traffic data for accurate classification, which …

Nowadays, most Internet communications have adopted encrypted network access
technology for privacy protection, so encrypted traffic classification (ETC) has become a …

Deep learning (DL) has been successfully applied to encrypted network traffic classification
in experimental settings. However, in production use, it has been shown that a DL classifier's …

As the size and source of network traffic increase, so does the challenge of monitoring and
analyzing network traffic. The challenging problems of classifying encrypted traffic are the …

With the rapid development of the network, encrypted traffic classification plays a vital role in
guaranteeing the quality of network services and ensuring the security of the network …