Exploring the online underground marketplaces through topic-based social network and clustering

Shin Ying Huang, Hsinchun Chen

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

3 Citations (Scopus)

Abstract

Cyber fraud causes significant losses to the economy and has become a lucrative form of illicit business by leveraging the Internet as a communication channel. Criminals in the cyber fraud underground economy use online underground marketplaces and other forms of social media to exchange information and trade stolen information. Analyzing these underground marketplaces is challenging due to the variability of both members and marketplaces. To understand more about the underground economy and the actors in it, we propose a topic-based social network analysis and clustering approach to identify the key members and their roles in the cyber fraud value chain. An experiment is conducted using data from several online underground marketplaces in China. Results suggest that the proposed method can aid in identifying key members in terms of roles, influence levels, and their social relationships.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Intelligence and Security Informatics: Cybersecurity and Big Data, ISI 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages145-150
Number of pages6
ISBN (Electronic)9781509038657
DOIs
StatePublished - Nov 15 2016
Event14th IEEE International Conference on Intelligence and Security Informatics, ISI 2015 - Tucson, United States
Duration: Sep 28 2016Sep 30 2016

Other

Other14th IEEE International Conference on Intelligence and Security Informatics, ISI 2015
CountryUnited States
CityTucson
Period9/28/169/30/16

Fingerprint

Electric network analysis
Internet
Industry
Experiments
Social networks
Clustering
Fraud
Underground economy

Keywords

  • black market
  • clustering
  • cyber threat intelligence
  • cybersecurity
  • social media analytics
  • social network
  • underground marketplaces

ASJC Scopus subject areas

  • Information Systems
  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality

Cite this

Huang, S. Y., & Chen, H. (2016). Exploring the online underground marketplaces through topic-based social network and clustering. In IEEE International Conference on Intelligence and Security Informatics: Cybersecurity and Big Data, ISI 2016 (pp. 145-150). [7745458] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISI.2016.7745458

Exploring the online underground marketplaces through topic-based social network and clustering. / Huang, Shin Ying; Chen, Hsinchun.

IEEE International Conference on Intelligence and Security Informatics: Cybersecurity and Big Data, ISI 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 145-150 7745458.

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

Huang, SY & Chen, H 2016, Exploring the online underground marketplaces through topic-based social network and clustering. in IEEE International Conference on Intelligence and Security Informatics: Cybersecurity and Big Data, ISI 2016., 7745458, Institute of Electrical and Electronics Engineers Inc., pp. 145-150, 14th IEEE International Conference on Intelligence and Security Informatics, ISI 2015, Tucson, United States, 9/28/16. https://doi.org/10.1109/ISI.2016.7745458
Huang SY, Chen H. Exploring the online underground marketplaces through topic-based social network and clustering. In IEEE International Conference on Intelligence and Security Informatics: Cybersecurity and Big Data, ISI 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 145-150. 7745458 https://doi.org/10.1109/ISI.2016.7745458
Huang, Shin Ying ; Chen, Hsinchun. / Exploring the online underground marketplaces through topic-based social network and clustering. IEEE International Conference on Intelligence and Security Informatics: Cybersecurity and Big Data, ISI 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 145-150
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