Detecting Potential Insider Threat: Analyzing Insiders' Sentiment Exposed in Social Media

Won Park, Youngin You, Kyungho Lee

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)


In the era of Internet of Things (IoT), impact of social media is increasing gradually. With the huge progress in the IoT device, insider threat is becoming much more dangerous. Trying to find what kind of people are in high risk for the organization, about one million of tweets were analyzed by sentiment analysis methodology. Dataset made by the web service "Sentiment140" was used to find possible malicious insider. Based on the analysis of the sentiment level, users with negative sentiments were classified by the criteria and then selected as possible malicious insiders according to the threat level. Machine learning algorithms in the open-sourced machine learning software "Weka (Waikato Environment for Knowledge Analysis)" were used to find the possible malicious insider. Decision Tree had the highest accuracy among supervised learning algorithms and K-Means had the highest accuracy among unsupervised learning. In addition, we extract the frequently used words from the topic modeling technique and then verified the analysis results by matching them to the information security compliance elements. These findings can contribute to achieve higher detection accuracy by combining individual's characteristics to the previous studies such as analyzing system behavior.

Original languageEnglish
Article number7243296
JournalSecurity and Communication Networks
Publication statusPublished - 2018

Bibliographical note

Funding Information:
This research was supported by the MSIT (Ministry of Science, ICT), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2018-2015-0-00403) supervised by the IITP (Institute for Information and communications Technology Promotion).

Publisher Copyright:
© 2018 Won Park et al.

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications


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