Money Laundering Detection with Node2Vec

Home Page
About
Submit A Journal
Submit A Conference
Submit Paper/Book
- Submit a Preprint
- Submit a Book
Contact

Gazi University Journal of Science
Volume:35 Issue:3
Money Laundering Detection with Node2Vec

Money Laundering Detection with Node2Vec

Authors : Mehmet ÇAĞLAYAN, Şerif BAHTİYAR

Pages : 854-873

Doi:10.35378/gujs.854725

View : 57 | Download : 11

Publication Date : 2022-09-01

Article Type : Research Paper

Abstract :The widespread use of computing technology has been changing relationships among people in societies. Criminals are aware of the power of the technology so that many criminal activities involve more computing systems. Money laundering has been a significant criminal activity within financial computing systems for many decades. The dynamic nature of information systems has reduced the effectiveness of existing money laundering detection mechanisms that is an important challenge for societies. In this paper, we consider machine learning algorithms as complementary solutions to existing money laundering detection mechanisms. We have focused on graph-based representation of data with Node2Vec to have better classification results for money laundering detections with machine learning algorithms. Our experimental analyses show that Node2Vec enable us to select the most convenient machine learning algorithm for money laundering detections.
Keywords : Money laundering, Machine learning, Financial transaction, Security

ORIGINAL ARTICLE URL

* There may have been changes in the journal, article,conference, book, preprint etc. informations. Therefore, it would be appropriate to follow the information on the official page of the source. The information here is shared for informational purposes. IAD is not responsible for incorrect or missing information.