Active discovery of hidden profiles in social networks using malware

Abstract

In this study we investigate the problem of diffusion in social networks, an issue which is relevant in areas such as cyber intelligence. Contrary to related work that focuses on the identification of invisible areas of a social network, our work focuses on finding the most effective nodes for placing seeds in order to effectively reveal hidden nodes in a focused manner. The seeds may consist of malware that propagates in social networks and is capable of revealing hidden invisible nodes. The malware has only limited time to function and operate in stealth mode so as not to alert the hidden node, thus there is a need to identify and utilize the visible nodes that are most effective at spreading the malware across the hidden nodes with minimal effect on the visible nodes. We empirically evaluate the ability of the Weighted Closeness metric (WC) among visible nodes to improve diffusion focus and reach invisible nodes in a social network. Experiments performed with a variety of social network topologies validated the effectiveness of the proposed method.