Wangiri fraud: Pattern analysis and machine-learning-based detection

A Ravi, M Msahli, H Qiu, G Memmi… - IEEE Internet of …, 2022 - ieeexplore.ieee.org
The rapid growth of the telecommunication landscape leads to a rapid rise of frauds in such
networks. In this article, Wangiri fraud in which users are deceived by being charged for …

Detection of wangiri telecommunication fraud using ensemble learning

M Arafat, A Qusef, G Sammour - 2019 IEEE Jordan International …, 2019 - ieeexplore.ieee.org
Fraudsters can manipulate telecom regulatory systems to their advantage, and to the
disadvantage of the telecom operator, in ways that are difficult to detect, trace, and …

Detection and analysis of fraud phone calls using artificial intelligence

S Malhotra, G Arora, R Bathla - 2023 International Conference …, 2023 - ieeexplore.ieee.org
With an increase advancement of technology, fraud phone calls, including spams and
malicious calls have become a major concern in telecommunication industry and causes …

An incremental identification method for fraud phone calls based on broad learning system

R Zhong, X Dong, R Lin, H Zou - 2019 IEEE 19th International …, 2019 - ieeexplore.ieee.org
With the continuous development of the communication industry, more and more fraud calls
appear in the user's daily life and the crime of telecom fraud is growing rapidly, causing …

Anomaly pattern analysis based on machine learning on real telecommunication data

HH Kilinc - 2022 7th International Conference on Computer …, 2022 - ieeexplore.ieee.org
Fraud and anomalies are serious problems in the telecommunication world. These problems
can be detected with the machine learning based tools. In this study, we used a Call Detail …

Convnets for fraud detection analysis

A Chouiekh, ELHIEL Haj - Procedia Computer Science, 2018 - Elsevier
Fraud activity is a big concern for telecom companies. The advances in technology and
system information have significantly increased fraud activities, which can have negative …

Automated fraudulent phone call recognition through deep learning

J Xing, M Yu, S Wang, Y Zhang… - … and Mobile Computing, 2020 - Wiley Online Library
Several studies have shown that the phone number and call behavior generated by a phone
call reveal the type of phone call. By analyzing the phone number rules and call behavior …

Machine learning techniques for sim box fraud detection

M Kashir, S Bashir - 2019 International Conference on …, 2019 - ieeexplore.ieee.org
In today's competitive environment, telecommunication operators and service providers
need to generate revenue by designing and delivering innovative services to the …

K-means algorithm: fraud detection based on signaling data

X Min, R Lin - 2018 IEEE World congress on services …, 2018 - ieeexplore.ieee.org
At present, the crime of telecom fraud, with advanced communications and Internet
technologies, is growing rapidly and causing huge losses every year. The traditional fraud …

Nature-inspired techniques in the context of fraud detection

M Behdad, L Barone, M Bennamoun… - IEEE Transactions on …, 2012 - ieeexplore.ieee.org
Electronic fraud is highly lucrative, with estimates suggesting these crimes to be worth
millions of dollars annually. Because of its complex nature, electronic fraud detection is …