  The study of network robustness focuses on the way the overall functionality
of a network is affected as some of its constituent parts fail. Failures can
occur at random or be part of an intentional attack and, in general, networks
behave differently against different removal strategies. Although much effort
has been put on this topic, there is no unified framework to study the problem.
While random failures have been mostly studied under percolation theory,
targeted attacks have been recently restated in terms of network dismantling.
In this work, we link these two approaches by performing a finite-size scaling
analysis to four dismantling strategies over Erd\"{o}s-R\'enyi networks:
initial and recalculated high degree removal and initial and recalculated high
betweenness removal. We find that the critical exponents associated with the
initial attacks are consistent with the ones corresponding to random
percolation, while the recalculated attacks are likely to belong to different
universality classes. In particular, recalculated betweenness produces a very
abrupt transition with a hump in the cluster size distribution near the
critical point, resembling some explosive percolation processes.
