The extensive research in machine learning based Android malware detection showcases
high-performance metrics through a wide range of proposed solutions. Consequently, this …

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 …

The emerging programmable networks sparked significant research on Intelligent Network
Data Plane (INDP), which achieves learning-based traffic analysis at line-speed. Prior art in …

Intrusion detection is a critical field in network security research that is devoted to detecting
malicious traffic or attacks on networks. Even with the advances in today's Internet …

Traffic classification is a critical task in network security and management. Recent research
has demonstrated the effectiveness of the deep learning-based traffic classification method …

Network security situational awareness is based on the extraction and analysis of big data,
and by understanding these data to evaluate the current network security status and predict …

In recent years, the use of TLS (Transport Layer Security) protocol to protect communication
information has become increasingly popular as users are more aware of network security …

With the increasing complexity of network protocol traffic in the modern network
environment, the task of traffic classification is facing significant challenges. Existing …

Due to the limitations of the existing annotation methods, the prevalence of label noise can
be caused in realistic malicious traffic datasets, which has a significant impact on the training …

Network traffic classification plays a crucial role in network security and network quality of
service. The new emerging traffic data in the real world is unlabeled and may contain …