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

Software system complexity and security vulnerability diversity are plausible sources of the
persistent challenges in software vulnerability research. Applying deep learning methods for …

Ever since its genesis, Android has enabled apps to access data and services on mobile
devices. This however involves a wide variety of user-unresettable identifiers (UUIs), eg, the …

Browser extensions have emerged as integrated characteristics in modern browsers, with
the aim to boost the online browsing experience. Their advantageous position between a …

Mini-programs (MiniApps), lightweight versions of full-featured mobile apps that run inside a
host app such as WeChat, have become increasingly popular due to their simplified and …

Deep Neural Networks (DNNs) have been widely adopted, yet DNN models are surprisingly
unreliable, which raises significant concerns about their use in critical domains. In this work …

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 …

The attacks and defenses on the information of which website pages are visited by users are
important research subjects in the field of privacy enhancing technologies, they are termed …

This paper proposes FingerprinTV, a fully automated methodology for extracting fingerprints
from the network traffic of smart TV apps and assessing their performance. FingerprinTV (1) …

Trained with a sufficiently large training and testing dataset, Deep Neural Networks (DNNs)
are expected to generalize. However, inputs may deviate from the training dataset …