  Social Network Analysis (SNA) is an interdisciplinary science that focuses on
discovering the patterns of individuals interactions. In particular,
practitioners have used SNA to describe and analyze criminal networks to
highlight subgroups, key actors, strengths and weaknesses in order to generate
disruption interventions and crime prevention systems. In this paper, the
effectiveness of a total of seven disruption strategies for two real Mafia
networks is investigated adopting SNA tools. Three interventions targeting
actors with a high level of social capital and three interventions targeting
those with a high human capital are put to the test and compared between each
other and with random node removal. Human and social capital approaches were
also applied on the Barab\'asi-Albert models which are the one which better
represent criminal networks. Simulations showed that actor removal based on
social capital proved to be the most effective strategy, by leading to the
total disruption of the criminal network in the least number of steps. The
removal of a specific figure of a Mafia family such as the Caporegime seemed
also promising in the network disruption.
