Analysis and Detection of Fraud in Email Database Using Machine Learning Approach

Volume 20 No 7 (2022)

SANDEEP B L,SIDDESH G M

DOI: 10.14704/nq.2022.20.7.NQ33366

Abstract

The email has been one of the most widespread communication forms used in the business in recent times, resulting in misusing communication for one's gain or faking the identity. Fraud detection is a set of activities undertaken to prevent money or property from being obtained through pretenses

Keywords

Email, social network analysis, community detection, boosting, iterative prediction, Email visualization.

Copyright © Neuroquantology

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Articles published in the Neuroquantology are available under Creative Commons Attribution Non-Commercial No Derivatives Licence (CC BY-NC-ND 4.0). Authors retain copyright in their work and grant IJECSE right of first publication under CC BY-NC-ND 4.0. Users have the right to read, download, copy, distribute, print, search, or link to the full texts of articles in this journal, and to use them for any other lawful purpose.