@inproceedings{1d7a7ccdccda47d8b32199ff23095d97,
title = "Link Analysis and Shortest Path Algorithm for Money Laundry Detection",
abstract = "Money laundering is a process where money from illegal sources is transferred through fraud and concealment to make it appear as legal and legitimate. It is estimated that 2-5% of global GDP is laundered every year. The identification of suspects involved in the laundering network is significantly challenging. This work reports on the utilization of a modified method to identify further money laundering nodes starting with two prior identified suspects. Link analysis was used to transform the weight of the link in a money laundering network starting with two suspects into a distance measured in a new graph representation. The shortest-path algorithm was then utilized to identify the optimal path between two nodes, which cannot be used directly to necessarily identify the strongest association between the pair of nodes. The results show that this method is efficient when large data sets are investigated and when data structure involves minimal attributes to start with.",
keywords = "Dijkstra's Algorithm, Link analysis, money laundry, shortest path",
author = "Mansoor Al-Thani and Dena Al-Thani",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 International Symposium on Networks, Computers and Communications, ISNCC 2023 ; Conference date: 23-10-2023 Through 26-10-2023",
year = "2023",
doi = "10.1109/ISNCC58260.2023.10323858",
language = "English",
series = "2023 International Symposium on Networks, Computers and Communications, ISNCC 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2023 International Symposium on Networks, Computers and Communications, ISNCC 2023",
address = "United States",
}