The study of network robustness is a critical tool in the characterization and sense making of
complex interconnected systems such as infrastructure, communication and social networks …

Graph robustness metrics have been used largely to study the behavior of communication
networks in the presence of targeted attacks and random failures. Several researchers have …

Spectral measures have long been used to quantify the robustness of real-world graphs. For
example, spectral radius (or the principal eigenvalue) is related to the effective spreading …

Research on the robustness of networks, and in particular the Internet, has gained critical
importance in recent decades because more and more individuals, societies and firms rely …

Network robustness is critical for various industrial and social networks against malicious
attacks, which has various meanings in different research contexts and here it refers to the …

Society relies heavily on its networked physical infrastructure and information systems.
Accurately assessing the vulnerability of these systems against disruptive events is vital for …

Network measures derived from empirical observations are often poor estimators of the true
structure of system as it is impossible to observe all components and all interactions in many …

We describe a suite of metrics for measuring network-wide cyber security risk based on a
model of multi-step attack vulnerability (attack graphs). Our metrics are grouped into families …

Recent studies have shown that Graph Convolutional Networks (GCNs) are vulnerable to
adversarial attacks on the graph structure. Although multiple works have been proposed to …

The robustness is an important functionality of networks because it manifests the ability of
networks to resist failures or attacks. Many robustness measures have been proposed from …