  In this article we present the Hayastan Shakarian (HS), a robustness index
for complex networks. HS measures the impact of a network disconnection (edge)
while comparing the sizes of the remaining connected components. Strictly
speaking, the Hayastan Shakarian index is defined as edge removal that produces
the maximal inverse of the size of the largest connected component divided by
the sum of the sizes of the remaining ones.
  We tested our index in attack strategies where the nodes are disconnected in
decreasing order of a specified metric. We considered using the Hayastan
Shakarian cut (disconnecting the edge with max HS) and other well-known
strategies as the higher betweenness centrality disconnection. All strategies
were compared regarding the behavior of the robustness (R-index) during the
attacks. In an attempt to simulate the internet backbone, the attacks were
performed in complex networks with power-law degree distributions (scale-free
networks).
  Preliminary results show that attacks based on disconnecting using the
Hayastan Shakarian cut are more dangerous (decreasing the robustness) than the
same attacks based on other centrality measures. We believe that the Hayastan
Shakarian cut, as well as other measures based on the size of the largest
connected component, provides a good addition to other robustness metrics for
complex networks.
