Parallel and incremental credit card fraud detection model to handle concept drift and data imbalance
Sign Up to like & getrecommendations! Published in 2018 at "Neural Computing and Applications"
DOI: 10.1007/s00521-018-3633-8
Abstract: Real-time fraud detection in credit card transactions is challenging due to the intrinsic properties of transaction data, namely data imbalance, noise, borderline entities and concept drift. The advent of mobile payment systems has further complicated… read more here.
Keywords: fraud detection; model; credit card; data imbalance ... See more keywords
Customs fraud detection
Sign Up to like & getrecommendations! Published in 2019 at "Pattern Analysis and Applications"
DOI: 10.1007/s10044-019-00852-w
Abstract: In this customs fraud detection application, we analyse a unique data set of 9,624,124 records resulting from a collaboration with the Belgian customs administration. They are faced with increasing levels of international trade, which pressurizes… read more here.
Keywords: fraud detection; methodology; fraud; customs fraud ... See more keywords
Fraud detection for job placement using hierarchical clusters-based deep neural networks
Sign Up to like & getrecommendations! Published in 2019 at "Applied Intelligence"
DOI: 10.1007/s10489-019-01419-2
Abstract: Fraud detection is becoming an integral part of business intelligence, as detecting fraud in the work processes of a company is of great value. Fraud is an inhibitory factor to accurate appraisal in the evaluation… read more here.
Keywords: deep neural; neural networks; hierarchical clusters; fraud detection ... See more keywords
Election Forensics: Quantitative methods for electoral fraud detection.
Sign Up to like & getrecommendations! Published in 2019 at "Forensic science international"
DOI: 10.1016/j.forsciint.2018.11.010
Abstract: The last decade has witnessed an explosion on the computational power and a parallel increase of the access to large sets of data - the so called Big Data paradigm - which is enabling to… read more here.
Keywords: forensics quantitative; fraud detection; election forensics;
A subgraph-based knowledge reasoning method for collective fraud detection in E-commerce
Sign Up to like & getrecommendations! Published in 2021 at "Neurocomputing"
DOI: 10.1016/j.neucom.2021.03.134
Abstract: Abstract Fraud detection is essential for e-commerce platforms to maintain a fair business environment. Many existing works propose manually designed methods such as label propagation and dense block mining rules on built user-item graphs to… read more here.
Keywords: collective fraud; subgraph based; knowledge reasoning; fraud detection ... See more keywords
Cooperative Fraud Detection Model With Privacy-Preserving in Real CDR Datasets
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2935759
Abstract: The researchers have shown broad concern about detection and recognition of fraudsters since telecommunication operators and the individual user are both suffering significant losses from fraud activities. Researchers have proposed various solutions to counter fraudulent… read more here.
Keywords: fraud; model; fraud detection; privacy ... See more keywords
Online Recruitment Fraud Detection: A Study on Contextual Features in Australian Job Industries
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3197225
Abstract: The purpose of this study is to investigate the effects of contextual features on automatic detection accuracy of online recruitment frauds in Australian job market. In addition, the study aims to unearth the significance of… read more here.
Keywords: contextual features; fraud detection; online recruitment; study ... See more keywords
Robust Credit Card Fraud Detection Based on Efficient Kolmogorov-Arnold Network Models
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Access"
DOI: 10.1109/access.2024.3485200
Abstract: Credit card fraud detection remains a significant challenge in the financial industry, necessitating advanced models to identify fraudulent activities while minimizing false positives accurately. Traditional machine learning approaches, such as Multilayer Perceptrons (MLP), have been… read more here.
Keywords: fraud detection; fraud; card fraud; credit card ... See more keywords
An Integrated Preprocessing and Drift Detection Approach With Adaptive Windowing for Fraud Detection in Payment Systems
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Access"
DOI: 10.1109/access.2025.3569609
Abstract: As fraudulent transaction methods evolve rapidly; it becomes progressively more challenging to detect them in payment systems. Static machine learning and rule-based traditional detection methods cannot capture all the dynamic and evolving nature of fraudulent… read more here.
Keywords: detection; fraud detection; drift; drift detection ... See more keywords
AI Driven Fraud Detection Models in Financial Networks: A Comprehensive Systematic Review
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Access"
DOI: 10.1109/access.2025.3596060
Abstract: Rapid advancements in digital innovation and globalization has significantly increased the complexity of financial networks, making them more vulnerable to fraud. Traditional fraud detection methods struggle to keep pace with evolving fraudulent strategies, contributing to… read more here.
Keywords: detection; fraud detection; financial networks; review ... See more keywords
HearLiquid: Nonintrusive Liquid Fraud Detection Using Commodity Acoustic Devices
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2022.3144427
Abstract: Liquid fraud has plagued people with huge health risks. Liquid fraud detection can help to reduce the risk of liquid hazards. However, existing systems that use biochemical tools or radio frequency signals for liquid sensing… read more here.
Keywords: liquid fraud; fraud detection; detection; acoustic devices ... See more keywords