Phishing has become an increasing concern and captured the attention of end-users as well
as security experts. Existing phishing detection techniques still suffer from the deficiency in …

Multimodal classification research has been gaining popularity with new datasets in
domains such as satellite imagery, biometrics, and medicine. Prior research has shown the …

As people's demand for personal privacy and data security becomes a priority, encrypted
traffic has become mainstream in the cyber world. However, traffic encryption is also …

Real-time network inspection applications face a threat of vulnerability as high-speed
networks continue to expand. For companies and ISPs, real-time traffic classification is an …

With the rapid growth of Internet data traffic, the means of malicious attack become more
diversified. The single modal intrusion detection model cannot fully exploit the rich feature …

Classifying encrypted traffic from emerging applications is important but challenging as
many conventional traffic classification approaches are ineffective, thus calling for novel …

Traffic classification is one of the fundamental tasks in computer networking. This task aims
to associate network traffic to a specific class according to the requirements (eg, QoS …

Traditional machine learning models used for network intrusion detection systems rely on
vast amounts of network traffic data with expertly engineered features. The abundance of …

With the rapid development of the Internet of Things (IoT), numerous of IoT devices and
different characteristics in IoT traffic patterns need traffic classification to enable many …

The development of the Internet has led to the complexity of network encrypted traffic.
Identifying the specific classes of network encryption traffic is an important part of …