Using the spanning tree of a criminal network for identifying its leaders

Kamal Taha, Paul D. Yoo

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

Abstract

We introduce a forensic analysis system called ECLfinder that identifies the influential members of a criminal organization as well as the immediate leaders of a given list of lower-level criminals. Criminal investigators usually seek to identify the influential members of criminal organizations, because eliminating them is most likely to hinder and disrupt the operations of these organizations and put them out of business. First, ECLfinder constructs a network representing a criminal organization from either mobile communication data associated with the organization or crime incident reports that include information about the organization. It then constructs a minimum spanning tree (MST) of the network. It identifies the influential members of a criminal organization by determining the important vertices in the network representing the organization, using the concept of existence dependence. Each vertex v is assigned a score, which is the number of other vertices, whose existence in MST is dependent on v. Vertices are ranked based on their scores. Criminals represented by the top ranked vertices are considered the influential members of the criminal organization represented by the network. We evaluated the quality of ECLfinder by comparing it experimentally with three other systems. Results showed marked improvement.

Original languageBritish English
Article number2622226
Pages (from-to)445-453
Number of pages9
JournalIEEE Transactions on Information Forensics and Security
Volume12
Issue number2
DOIs
StatePublished - Feb 2017

Keywords

  • Criminal network
  • Digital forensic
  • Forensic investigation
  • Mobile communication data
  • Social network

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