Network traffic classification has long been a pivotal topic in network security. In the past two
decades, methods like port-based classification, deep packet inspection, and machine …

Website fingerprinting (WF) enables eavesdroppers to identify the website a user is visiting
by network surveillance, even if the traffic is protected by anonymous communication …

While streaming video has become a dominant form of information on the web, a number of
previous works have shown that encrypted streaming video is vulnerable to network traffic …

Encrypted traffic has been known to be vulnerable to traffic analysis attacks that exploit the
statistical features of encrypted traffic flows, such as packet sizes, timing, and direction, to …

Deep neural networks (DNNs) deployed in real-world applications can encounter out-of-
distribution (OOD) data and adversarial examples. These represent distinct forms of …

Traditional network intrusion detection systems excel at screening known attack types, but
face significant challenges when dealing with unseen malicious traffic, often misclassifying …

The machine learning communities, such as those around computer vision or natural
language processing, have developed numerous supportive tools and benchmark datasets …

Encrypted traffic has been known to be vulnerable to traffic analysis attacks that exploit the
statistical features of encrypted traffic flows, such as packet sizes, timing, and direction, to …