Given the distributed nature of the massively connected “Things” in IoT, IoT networks have
been a primary target for cyberattacks. Although machine learning based network intrusion …

Encrypted network traffic is the principal foundation of secure network communication, and it
can help ensure the privacy and integrity of confidential information. However, it hides the …

The popularity of 5G networks poses a huge challenge for malicious traffic detection
technology. The reason for this is that as the use of 5G technology increases, so does the …

For machine-learning-based network traffic classification, we usually need large number of
correctly labeled samples (ground truth) for model-training to get high accuracy. However in …

To manage and monitor their networks in a proper way, network operators are often
interested in identifying the applications generating the traffic traveling through their …

Profiling Internet backbone traffic is becoming an increasingly hard problem since users and
applications are avoiding detection using traffic obfuscation and encryption. The key …

While encryption enhances data security, it also presents significant challenges for network
traffic analysis, especially in detecting malicious activities. To tackle this challenge, this …

Traffic classification is the first step of network QoS control mechanism and traffic anomaly
detection and is an important research branch of congestion control and network security. In …

To manage and monitor their networks in a proper way, network operators are often
interested in automatic methods that enable them to identify applications generating the …

This paper proposes a novel non-parametric technique for clustering networks based on
their structure. Many topological measures have been introduced in the literature to …