A Prioritization Algorithm for Crime Busting based on Centrality Analysis

DOI

10.2991/emeit.2012.30How to use a DOI?

Keywords

Crime busting, Social network, Centrality, Sorting

Abstract

Detecting conspirators, which often relates to organized crimes, represents a major problem for many investigation bureaus. A prioritization algorithm based on centrality analysis was introduced. The correlation between suspects was modeled as a social network, and the degree, betweeness and eigenvector centralities were utilized to quantify the suspicion degree of individual conspirators. Due to the analysis, conspirators and non-conspirators were able to be sorted into high-suspected, low-suspected, low-unsuspected and high-unsuspected sections based on their likelihood of involving the conspiracy. A detailed scenario is studied and the efficacy of the given method is verified at the end of this paper.

Copyright

© 2012, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yundong Gu
AU  - Wentao Li
AU  - Liwen Zhang
AU  - Mingke Shen
AU  - Binglei Xie
PY  - 2012/09
DA  - 2012/09
TI  - A Prioritization Algorithm for Crime Busting based on Centrality Analysis
BT  - Proceedings of the 2nd International Conference on Electronic & Mechanical Engineering and Information Technology (EMEIT 2012)
PB  - Atlantis Press
SP  - 155
EP  - 159
SN  - 1951-6851
UR  - https://doi.org/10.2991/emeit.2012.30
DO  - 10.2991/emeit.2012.30
ID  - Gu2012/09
ER  -