Comparative Analysis of Back-propagation Neural Network and K-Means Clustering Algorithm in Fraud Detection in Online Credit Card Transactions by B.A. Abdulsalami, A. A. Kolawole, M.A. Ogunrinde, M. Lawal, R.A. Azeez, A.Z. Afolabi

“…Keywords: Credit card, Fraud detection, Back-Propagation neural network, Clustering algorithm, Machine learning, Security. …”
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Comparative Analysis of Back-propagation Neural Network and K-Means Clustering Algorithm in Fraud Detection in Online Credit Card Transactions by B.A. Abdulsalami, A. A. Kolawole, M.A. Ogunrinde, M. Lawal, R.A. Azeez, A.Z. Afolabi

“…Keywords: Credit card, Fraud detection, Back-Propagation neural network, Clustering algorithm, Machine learning, Security. …”
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RDQN: ensemble of deep neural network with reinforcement learning in classification based on rough set theory for digital transactional fraud detection by Chandana Gouri Tekkali, Karthika Natarajan

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EFN-SMOTE: An effective oversampling technique for credit card fraud detection by utilizing noise filtering and fuzzy c-means clustering by Hadeel Ahmad, Bassam Kasasbeh, Balqees AL-Dabaybah, Enas Rawashdeh

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A Fuzzy-SOM Method for Fraud Detection in Power Distribution Networks with High Penetration of Roof-Top Grid-Connected PV by Alireza Vahabzadeh, Alibakhsh Kasaeian, Hasan Monsef, Alireza Aslani

Subjects: “…fraud-detection…”
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Freeman chain code (FCC) representation in signature fraud detection based on nearest neighbour and artificial neural network (ANN) classifiers. by Azmi, Aini Najwa, Nasien, Dewi

CTCN: a novel credit card fraud detection method based on Conditional Tabular Generative Adversarial Networks and Temporal Convolutional Network by Xiaoyan Zhao, Shaopeng Guan

Subjects: “…Credit card fraud detection…”
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Scams and Solutions in Cryptocurrencies—A Survey Analyzing Existing Machine Learning Models by Lakshmi Priya Krishnan, Iman Vakilinia, Sandeep Reddivari, Sanjay Ahuja

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SYSTEM FOR DETECTION OF NATIONAL HEALTHCARE INSURANCE FRAUD BASED ON COMPUTER APPLICATION by Budi Santoso, Julita Hendrartini, Bambang Udji Djoko Rianto, Laksono Trisnantoro

Subjects: “…fraud detection…”
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Active Learning in the Detection of Anomalies in Cryptocurrency Transactions by Leandro L. Cunha, Miguel A. Brito, Domingos F. Oliveira, Ana P. Martins

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Using local outlier factor to detect fraudulent claims in auto insurance by Maryam Esna-Ashari, Farzan Khamesian, Farbod Khanizadeh

Subjects: “…unsupervised algorithm‎ fraud detection‎…”
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Wallet-Based Transaction Fraud Prevention Through LightGBM With the Focus on Minimizing False Alarms by Can Iscan, Osman Kumas, Fatma Patlar Akbulut, Akhan Akbulut

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Simultaneous Classification and Regression for Zakat Under-Reporting Detection by Mohamed Maher Ben Ismail, Nasser AlSadhan

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Risk Management in E-Commerce—A Fraud Study Case Using Acoustic Analysis through Its Complexity by Diego C. Nascimento, Bruno Barbosa, André M. Perez, Daniel O. Caires, Edgar Hirama, Pedro L. Ramos, Francisco Louzada

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Penerapan Skeptisisme Profesional Auditor Internal Pemerintah dalam Mendeteksi Kecurangan (Studi Kasus pada Auditor Perwakilan BPKP Provinsi Jawa Tengah) by Sarina Gabryela Aprilyanti Butar Butar, Halim Dedy Perdana

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Research on Integrated Learning Fraud Detection Method Based on Combination Classifier Fusion (THBagging): A Case Study on the Foundational Medical Insurance Dataset by Jibing Gong, Hekai Zhang, Weixia Du

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Quad division prototype selection-based k-nearest neighbor classifier for click fraud detection from highly skewed user click dataset by Deepti Sisodia, Dilip Singh Sisodia

“…The performance of QDPSKNN is evaluated on Fraud Detection in Mobile Advertising (FDMA) user-click dataset and fifteen other benchmark imbalanced datasets to test its generalizing behaviour. …”
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Building classification models from imbalanced fraud detection data / Terence Yong Koon Beh, Swee Chuan Tan and Hwee Theng Yeo by Terence, Yong Koon Beh, Swee, Chuan Tan, Hwee, Theng Yeo

“…This paper reports our experience in applying data balancing techniques to develop a classifier for an imbalanced real-world fraud detection data set. We evaluated the models generated from seven classification algorithms with two simple data balancing techniques. …”
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A Minimum Error-Based PCA for Improving Classifier Performance in Detecting Financial Fraud by Bayu Nur Pambudi, Silmi Fauziati, Indriana Hidayah

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Internal Control System On Fraud Prevention Moderate By Bugis Cultural Values by Rahayu Wiliana, Febby Rachmadani, Syamsuddin Syamsuddin, Nadhirah Nagu, Achmad Fadel Farid

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