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 …

Traffic analysis is the process of monitoring network activities, discovering specific patterns,
and gleaning valuable information from network traffic. It can be applied in various fields …

With the rapid evolution of network traffic diversity, the understanding of network traffic has
become more pivotal and more formidable. Previously, traffic classification and intrusion …

With the enhancement of network security awareness and excellent applicability of
encryption protocols, identifying encrypted traffic is a critical and fundamental task for many …

The application of machine learning for the detection of malicious network traffic has been
well researched over the past several decades; it is particularly appealing when the traffic is …

Network traffic classification serves as a building block for important tasks such as security
and quality of service management. The field has been studied for a long time, with many …

Traffic detection systems based on machine learning have been proposed to defend against
cybersecurity threats, such as intrusion attacks and malware. However, they did not take the …

Identifying threats contained within encrypted network traffic poses a unique set of
challenges. It is important to monitor this traffic for threats and malware, but do so in a way …

The goal of network intrusion detection is to inspect network traffic in order to identify threats
and known attack patterns. One of its key features is Deep Packet Inspection (DPI), that …

In this paper, we propose HyperVision, a realtime unsupervised machine learning (ML)
based malicious traffic detection system. Particularly, HyperVision is able to detect unknown …