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Information 2018, 9(11), 280; https://doi.org/10.3390/info9110280

Predicting Cyber-Events by Leveraging Hacker Sentiment

Information Sciences Institute, University of Southern California, Marina del Rey, CA 90292, USA
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Received: 22 August 2018 / Revised: 12 November 2018 / Accepted: 13 November 2018 / Published: 15 November 2018
(This article belongs to the Special Issue Darkweb Cyber Threat Intelligence Mining)
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Abstract

Recent high-profile cyber-attacks exemplify why organizations need better cyber-defenses. Cyber-threats are hard to accurately predict because attackers usually try to mask their traces. However, they often discuss exploits and techniques on hacking forums. The community behavior of the hackers may provide insights into the groups’ collective malicious activity. We propose a novel approach to predict cyber-events using sentiment analysis. We test our approach using cyber-attack data from two major business organizations. We consider three types of events: malicious software installation, malicious-destination visits, and malicious emails that surmounted the target organizations’ defenses. We construct predictive signals by applying sentiment analysis to hacker forum posts to better understand hacker behavior. We analyze over 400 K posts written between January 2016 and January 2018 on over 100 hacking forums both on the surface and dark web. We find that some forums have significantly more predictive power than others. Sentiment-based models that leverage specific forums can complement state-of-the-art time-series models on forecasting cyber-attacks weeks ahead of the events. View Full-Text
Keywords: sentiment analysis; cyber-security; dark web sentiment analysis; cyber-security; dark web
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Deb, A.; Lerman, K.; Ferrara, E. Predicting Cyber-Events by Leveraging Hacker Sentiment. Information 2018, 9, 280.

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