In edge computing (EC), federated learning (FL) enables massive devices to collaboratively
train AI models without exposing local data. In order to avoid the possible bottleneck of the …

A new class of target link flooding attacks (LFAs) can cut off the Internet connections of a
target area without being detected, because they employ legitimate flows to congest …

A new class of target link flooding attacks (LFA) can cut off the Internet connections of a
target area without being detected because they employ legitimate flows to congest selected …

Traffic monitoring is a key enabler for several planning and management activities of a
Smart City. However, traditional techniques are often not cost efficient, flexible, and scalable …

In this paper, we study the problem of selecting paths to improve the performance of network
tomography applications in the presence of network element failures. We model the …

Calculating fine-grained link metrics by using aggregated path measurements, known as
network tomography, is an effective and efficient way to facilitate various network operations …

Network tomography is a powerful tool to monitor the internal state of a closed network that
cannot be measured directly, with broad applications in the Internet, overlay networks, and …

Network tomography is an attractive approach for inferring internal network states at edge
nodes. Recently, there is a growing interest in the basic understanding of the topological …

The launch of commercial 5G networks has unlocked numerous opportunities for heavy data
users and high-speed applications. The expected requirements for enhanced mobile …

Network tomography is a promising technique to achieve fault management in networks
where the existing IP-based troubleshooting mechanism cannot be used. Aiming to apply …