A Framework for Criminal Network Analysis Using Big Data

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

12 Scopus Citations
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Author(s)

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Detail(s)

Original languageEnglish
Title of host publicationProceedings - 13th IEEE International Conference on E-Business Engineering, ICEBE 2016 - Including 12th Workshop on Service-Oriented Applications, Integration and Collaboration, SOAIC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages17-23
ISBN (Print)9781509061198
Publication statusPublished - Nov 2016

Conference

Title13th IEEE International Conference on E-Business Engineering, ICEBE 2016
PlaceChina
CityMacau
Period4 - 6 November 2016

Abstract

Big data analytics have been proposed as a disruptive technology that will reshape security and law enforcement agencies, which is a domain that relies on data analytics to achieve criminal network insights for better decision-making. Rooted in current literature, we review the landscape of criminal network analysis through the big data analytic framework in this paper. We identify the big data sources, big data platforms, tools, and applications related to criminal network analysis. We then present some real-world examples, research challenges, and future research directions of applying big data analytics to the criminal analytics domain.

Research Area(s)

  • big data, criminal network, data mining, Social network analysis

Citation Format(s)

A Framework for Criminal Network Analysis Using Big Data. / Pramanik, Md Ileas; Zhang, Wenping; Lau, Raymond Y. K. et al.
Proceedings - 13th IEEE International Conference on E-Business Engineering, ICEBE 2016 - Including 12th Workshop on Service-Oriented Applications, Integration and Collaboration, SOAIC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 17-23.

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review