This study introduces a novel approach combining social network analysis with machine learning to predict future cyber threats by analyzing darkweb and deepweb hacking discussions. The method uses features from hacker social networks and cybersecurity advisories to predict software vulnerability exploitability. Experiments on real-world hacker and exploit data show that social network features significantly enhance prediction accuracy, improving recall by 19% and F1 score by 6%, while maintaining precision. The approach suggests that social network structures linked to exploit authors are key indicators of their future exploit activity.
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Almukaynizi, Mohammed, et al. "Predicting cyber threats through hacker social networks in darkweb and deepweb forums." Proceedings of the 2017 International Conference of The Computational Social Science Society of the Americas. 2017.
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