Predicting enterprise cyber incidents using social network analysis on dark web hacker forums
By Soumajyoti Sarkar, Mohammad Almukaynizi, Jana Shakarian, Paulo Shakarian
| December 09, 2019
With the 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 dark web forums by leveraging the reply network structure of user interactions with the goal of predicting enterprise cyberattacks. We use a suite of social network features on top of supervised learning models and validate them using 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, which gathered information from 53 forums on the dark web over a span of 12 months and attempted to predict real-world cyberattacks across 2 security incidents, that analyzing the path structure between groups of users is better than merely studying centralities like Pagerank or relying on user-posting statistics in forums.
Predicting enterprise cyber incidents using social network analysis on dark web hacker forums