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23 articles for “Fraud Detection”
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Research ArticleOpen accessPhrase in the titleComparative Analysis of Fraud Detection Methods in Banking Using Machine Learning TechniquesYoussef Tounsi, Ennouri TaziFraud detection in banking requires algorithms that balance classification performance, computational efficiency, and regulatory interpretability, criteria that are rarely benchmarked together. We present a comprehensive evaluation of nine machine learning approaches (Logistic Regression, Decision Tree, Random Forest, SVM, SGD, XGBoost, CatBoost, LightGBM, and MLP) across three datasets differing in size, imbalance severity, and feature type (synthetic, real-world PCA-anonymized, and large-scale … …Journal of Computer Science, Vol. 22, Issue 6 · 22 Jun 2026 · 1,341 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleOptimized XGBoost for Ethereum Fraud Detection: A Cost-Sensitive ApproachSupriya P., Rubah Sheriff, Shreya Padaki et al.In today’s technologically advancing world, many fields from finance to healthcare and education are shifting toward a digital and decentralized format. A significant transformation is underway with the currency of the masses. Blockchain-based cryptocurrencies like Bitcoin and Ethereum allow users to generate fungible tokens anonymously through smart contracts. However, these features also facilitate illicit transactions and cybercrimes like fraud, phishing, … …Journal of Computer Science, Vol. 21, Issue 12 · 10 Jan 2026 · 2,770 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEnsemble Learning for Proactive Detection of Network-Intrusion-Based Insurance FraudBenjamin Asubam Weyori, Selorm Kofi Tagbo et al.We propose an ensemble learning pipeline that proactively integrates Stacking Feature Embedding (SFE) with Principal Component Analysis (PCA) and tree-based ensembles to proactively detect insurance fraud originating from network intrusions. The main contributions are: (1) the novel integration of SFE-PCA as a meta-feature construction step for tabular network flow data; (2) a sensitivity analysis that justifies PCA reduction ratios used … …Journal of Computer Science, Vol. 22, Issue 7 · 16 Jul 2026 · 935 accessesView PDFCite
Review ArticleOpen accessEvery word in the titleMachine Learning-Based Detection of Credit Card Fraud: A Comparative StudyZainab Khamees Alkhateeb, Abeer Tariq MaoloodOne of the fastest-growing problems with a high impact on the financial sector is financial fraud. Recently, data mining has been identified as one of the effective ways of detecting fraudulent credit card transactions. As a data mining problem, the detection of fraudulent credit card transaction is a challenging task due to the following reasons: (i) The frequent changes in … …American Journal of Engineering and Applied Sciences, Vol. 12, Issue 4 · 25 Dec 2019 · 7,780 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA DATA WAREHOUSE DESIGN FOR THE DETECTION OF FRAUD IN THE SUPPLY CHAIN BY USING THE BENFORD’S LAWCornelia Kraus, Raul ValverdeLarge data volumes and the inability to analyse them enables fraudulent activities to go unnoticed in supply chain management processes such as procurement, warehouse management and inventory management. This fraud increases the cost of the supply chain management and a fraud detection mechanism is necessary to reduce the risk of fraud in this business area. This study was carried out … …American Journal of Applied Sciences, Vol. 11, Issue 9 · 7 Jul 2014 · 8,740 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleDetection of Commercial Fraud in Processed Meat Products Using Rapid TechniquesAli M. Ahmed, Takwa H. Ismail, Reham R. Abouelmaatti et al.Meat adulteration with different species has become a considerable problem worldwide. It means that meat products contain undeclared meat species; so, the meat ingredients are not consistent with the label. It has direct impact on public health, religious faith, fair-trades and food safety standers. This study focused on species adulteration detection in meat products by applying accurate, slandered and fast … …American Journal of Biochemistry and Biotechnology, Vol. 16, Issue 2 · 4 Jun 2020 · 7,817 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDetection and Solutions for Non-Technical Losses in Cameroon Electricity NetworkLekini Nkodo Claude Bernard, Ndzana Benoît, Oumarou Hamandjoda, Fippo Fitime LouisThe purpose of this study was to provide a tool to detect NTLs and subsequently, discuss the establishment of a prepaid system in Cameroon. The conception of a prepayment system for electric power or other utility commodity distribution using Wi-Fi and GSM to store and transfer value (money or KWh, meters reading indexes) from the client module to cut-off module … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 1 · 25 Jan 2018 · 7,370 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEvaluation of Customer Behaviour Irregularities in Cameroon Electricity Network using Support Vector MachineLekini Nkodo Claude Bernard, Ndzana Benoît, Oumarou HamandjodaNon-Technical Losses (NTLs) in the Cameroonians electricity network are approximately 30 to 40% of production and are estimated at several billion CFA francs per year for National Electricity Company (ENEO); Hence the importance of finding effective solutions to fight against these losses. The purpose of this work was to develop a tool for the fraud detection for Cameroon National Electricity … …American Journal of Engineering and Applied Sciences, Vol. 10, Issue 1 · 6 Jan 2017 · 7,544 accessesView PDFCite
Review ArticleOpen accessIn the keywordsBig Data in Medical Applications and Health CareLidong Wang, Cheryl Ann AlexanderBig Data can unify all patient related data to get a 360-degree view of the patient to analyze and predict outcomes. It can improve clinical practices, new drug development and health care financing process. It offers a lot of benefits such as early disease detection, fraud detection and better healthcare quality and efficiency. This paper introduces the Big Data concept … …Current Research in Medicine, Vol. 6, Issue 1 · 15 May 2015 · 14,953 accessesView PDFCite
Research ArticleOpen accessIn the keywordsProbabilistic Learning Models for Secure E-Commerce Transaction AnalysisAnanth Maria Pushpa, S. SubramaniaanThe tremendous expansion of e-commerce requires well-developed security mechanisms of transactions coupled with cryptography systems. This paper explores how probabilistic learning algorithms can be used to promote fraud and transaction validation in e-commerce systems that are cryptographically secured. A study compared different machine learning models to analyze retail data, including Naïve Bayes, Bayes Network, and Logistic learning. The results showed … …Journal of Computer Science, Vol. 22, Issue 11 · 20 Oct 2026 · 506 accessesView PDFCite