  With rise in security breaches over the past few years, there has been an
increasing need to mine insights from social media platforms to raise alerts of
possible attacks in an attempt to defend conflict during competition. We use
information from the darkweb forums by leveraging the reply network structure
of user interactions with the goal of predicting enterprise cyber attacks. We
use a suite of social network features on top of supervised learning models and
validate them on a binary classification problem that attempts to predict
whether there would be an attack on any given day for an organization. We
conclude from our experiments using information from 53 forums in the darkweb
over a span of 12 months to predict real world organization cyber attacks of 2
different security events that analyzing the path structure between groups of
users is better than just studying network centralities like Pagerank or
relying on the user posting statistics in the forums.
