Fraud detection system: A survey

A Abdallah, MA Maarof, A Zainal - Journal of Network and Computer …, 2016 - Elsevier
The increment of computer technology use and the continued growth of companies have
enabled most financial transactions to be performed through the electronic commerce …

Mining fraudsters and fraudulent strategies in large-scale mobile social networks

Y Yang, Y Xu, Y Sun, Y Dong, F Wu… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
The rapid development of modern communication technologies-in particular,(mobile) phone
communications-has largely facilitated human social interactions and information exchange …

Fraudetector: A graph-mining-based framework for fraudulent phone call detection

VS Tseng, JC Ying, CW Huang, Y Kao… - Proceedings of the 21th …, 2015 - dl.acm.org
In recent years, fraud is increasing rapidly with the development of modern technology and
global communication. Although many literatures have addressed the fraud detection …

Hidden Markov models: an insight

MIM Yusoff, I Mohamed… - Proceedings of the 6th …, 2014 - ieeexplore.ieee.org
Hidden Markov models (HMM) is a probabilistic model consisting of variables representing
observations, variables that are hidden, the initial state distribution, transition matrix, and …

Cooperative Fraud detection model with privacy-preserving in real CDR datasets

N Ruan, Z Wei, J Liu - IEEE Access, 2019 - ieeexplore.ieee.org
The researchers have shown broad concern about detection and recognition of fraudsters
since telecommunication operators and the individual user are both suffering significant …

PFrauDetector: a parallelized graph mining approach for efficient fraudulent phone call detection

JJC Ying, J Zhang, CW Huang… - 2016 IEEE 22nd …, 2016 - ieeexplore.ieee.org
In recent years, fraud is becoming more rampant internationally with the development of
modern technology and global communication. Due to the rapid growth in the volume of call …

AI-JasCon: An Artificial Intelligent Containerization System for Bayesian Fraud Determination in Complex Networks

EO Nonum, KC Okafor, IAA Nosike, S Misra - Artificial Intelligence for …, 2022 - Springer
The post-COVID-19 era will create major financial losses in organizational resources as a
result of fraudulent activities by malicious agents existing at the edge and cloud domains …

Detection of bypass fraud based on speaker recognition

OM Elrajubi, AM Elshawesh… - 2017 8th International …, 2017 - ieeexplore.ieee.org
In telecommunication industry, fraud becomes a serious problem that affects
telecommunications service providers all around the world. As a significant amount of …

Engineering Detection Using Machine Learning

F Yahya, FSF Sze, LP Hung - Proceedings of the 13th National …, 2024 - books.google.com
Social engineering through online conversations can occur via phone calls, Skype, or
Google Meet, among others. This paper presents a machine learning-based classifier for …

Revisión Comparativa de Técnicas de Detección de Outliers en Aplicaciones Empresariales: Un Enfoque Práctico

C Rebollo Monjo - 2024 - repositorio.comillas.edu
En la actualidad, la sociedad está rodeada de una cantidad sin precedentes de datos que,
si se utilizan adecuadamente, pueden proporcionar información valiosa y servir como una …