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 …

With the increasing complexity and scale of modern networks, the demand for transparent
and interpretable Artificial Intelligence (AI) models has surged. This survey comprehensively …

Developing generalizable ML-based solutions for disparate learning problems in network
security is highly desired. However, despite a rich history of applying ML to network security …

Container overlay network, though being widely adopted to enable communication between
containers on different hosts, is a key downside for latency-sensitive applications. The state …

This paper introduces PPT, a pragmatic transport that achieves comparable performance to
proactive transports while maintaining good deployability as reactive transports. Our key …

Network traffic monitoring using IP flows is used to handle the current challenge of analyzing
encrypted network communication. Nevertheless, the packet aggregation into flow records …

Encrypted traffic detection and classification is a critical domain in network security,
increasingly essential in an era of pervasive encryption. This survey paper delves into …

Recently, uncertainty-aware deep learning methods for multiclass labeling problems have
been developed that provide calibrated class prediction probabilities and out-of-distribution …

The increasing popularity of online services has made Internet Traffic Classification a critical
field of study. However, the rapid development of internet protocols and encryption limits …

The accurate identification of internet traffic is crucial for network management. However, the
use of encryption techniques and constant changes in network protocols make it difficult to …