With the emergence of Online Social Networks (OSNs), as the most popular medium for advertisements, as source of knowledge and information, the emergence of malicious contents (viruses, false rumors, etc..) has become a critical issue that requires immediate attention. In this study we investigate on blocking the contagion of malicious things dynamically, by continuously fighting the diffusion near the source of misinformation under the Susceptible-Infectious-Recovered (SIR) model. We focus on protecting networked populations by removing key connections between nodes, and show via experimental results, that by following the infection the contagion can be controlled more efficiently and even being stopped in the earliest steps. We modify a well studied heuristic from the literature of graphs, and show that our proposed technique significantly outperforms what we believe the state-of-the-art competitors by successfully confronting the infection in real networks.
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