Criminal minds: Reasoning prime suspect in Russian hacking scandal by perspective of insiders

Mookyu Park, Junwoo Seo, Kyoungmin Kim, Moosung Park, Kyung Ho Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recent cyber attacks are affecting the cyberspace as well as the real world, causing social confusion. Russia Scandal in the US presidential election in 2016 is a representative example. This case is being discussed up to the impeachment of the president. Cyber influence attacks are attacks that affect cyberspace to real space. An effectiveness of such attacks boosts when insiders execute. This study analyzed the keywords related to cyber attacks of Russia during the US presidential election in 2016. Based on this, the paper used sentiment analysis for analyzing the psychology of the current Russian scandal suspect.

Original languageEnglish
Title of host publicationMIST 2017 - Proceedings of the 2017 International Workshop on Managing Insider Security Threats, co-located with CCS 2017
PublisherAssociation for Computing Machinery, Inc
Pages97-100
Number of pages4
Volume2017-January
ISBN (Electronic)9781450351775
DOIs
Publication statusPublished - 2017 Oct 30
Event9th ACM CCS International Workshop on Managing Insider Security Threats, MIST 2017 - Dallas, United States
Duration: 2017 Oct 30 → …

Other

Other9th ACM CCS International Workshop on Managing Insider Security Threats, MIST 2017
CountryUnited States
CityDallas
Period17/10/30 → …

Keywords

  • Insider's profiling
  • Russian scandal
  • Sentiment analysis
  • Topic model

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems

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  • Cite this

    Park, M., Seo, J., Kim, K., Park, M., & Lee, K. H. (2017). Criminal minds: Reasoning prime suspect in Russian hacking scandal by perspective of insiders. In MIST 2017 - Proceedings of the 2017 International Workshop on Managing Insider Security Threats, co-located with CCS 2017 (Vol. 2017-January, pp. 97-100). Association for Computing Machinery, Inc. https://doi.org/10.1145/3139923.3139936