Abstract

As networked and computer technologies continue to pervade all aspects of our lives, the threat from cyber attacks has also increased. However, detecting attacks, much less predicting them in advance, is a non-trivial task due to the anonymity of cyber attackers and the ambiguity of network data collected within an organization; often, by the time an attack pattern is recognized, the damage has already been done. Evidence suggests that the public discourse in external sources, such as news and social media, is often correlated with the occurrence of larger phenomena, such as election results or violent attacks. In this paper, we propose an approach that uses sentiment polarity as a sensor to analyze the social behavior of groups on social media as an indicator of cyber at-tack behavior. We developed an unsupervised sentiment prediction method that uses emotional signals to enhance the sentiment signal from sparse textual indicators. To explore the efficacy of sentiment polarity as an indicator of cyber-attacks, we performed experiments using real-world data from Twitter that corresponds to attacks by a well-known hacktivist group.

Original languageEnglish (US)
Title of host publicationAdvances in Human Factors, Business Management and Society - Proceedings of the AHFE 2018 International Conference on Human Factors, Business Management and Society, 2018
PublisherSpringer Verlag
Pages636-645
Number of pages10
ISBN (Print)9783319947082
DOIs
StatePublished - Jan 1 2019
EventAHFE International Conference on Human Factors, Business Management and Society, 2018 - [state] FL, United States
Duration: Jul 21 2018Jul 25 2018

Publication series

NameAdvances in Intelligent Systems and Computing
Volume783
ISSN (Print)2194-5357

Other

OtherAHFE International Conference on Human Factors, Business Management and Society, 2018
CountryUnited States
City[state] FL
Period7/21/187/25/18

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Keywords

  • Cybersecurity
  • Sentiment analysis
  • Social media analytics

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Sliva, A., Shu, K., & Liu, H. (2019). Using social media to understand cyber attack behavior. In Advances in Human Factors, Business Management and Society - Proceedings of the AHFE 2018 International Conference on Human Factors, Business Management and Society, 2018 (pp. 636-645). (Advances in Intelligent Systems and Computing; Vol. 783). Springer Verlag. https://doi.org/10.1007/978-3-319-94709-9_62