Ai-powered fraud detection in decentralized finance: A project life cycle perspective
Decentralized finance (DeFi) represents a novel financial system but faces significant fraud
challenges, leading to substantial losses. Recent advancements in artificial intelligence (AI) …
challenges, leading to substantial losses. Recent advancements in artificial intelligence (AI) …
Domain adaptation: challenges, methods, datasets, and applications
Deep Neural Networks (DNNs) trained on one dataset (source domain) do not perform well
on another set of data (target domain), which is different but has similar properties as the …
on another set of data (target domain), which is different but has similar properties as the …
An intelligent approach to credit card fraud detection using an optimized light gradient boosting machine
AA Taha, SJ Malebary - IEEE access, 2020 - ieeexplore.ieee.org
New advances in electronic commerce systems and communication technologies have
made the credit card the potentially most popular method of payment for both regular and …
made the credit card the potentially most popular method of payment for both regular and …
Ensemble of deep sequential models for credit card fraud detection
In the recent years, the fast development of e-commerce technologies made it possible for
people to select the most desirable items in terms of suggested price, quality and quantity …
people to select the most desirable items in terms of suggested price, quality and quantity …
[HTML][HTML] A supervised machine learning algorithm for detecting and predicting fraud in credit card transactions
Fraudsters are now more active in their attacks on credit card transactions than ever before.
With the advancement in data science and machine learning, various algorithms have been …
With the advancement in data science and machine learning, various algorithms have been …
Class balancing framework for credit card fraud detection based on clustering and similarity-based selection (SBS)
Credit card fraud is a growing problem nowadays and it has escalated during COVID-19 due
to the authorities in many countries requiring people to use cashless transactions. Every …
to the authorities in many countries requiring people to use cashless transactions. Every …
MOCCA: Multilayer one-class classification for anomaly detection
Anomalies are ubiquitous in all scientific fields and can express an unexpected event due to
incomplete knowledge about the data distribution or an unknown process that suddenly …
incomplete knowledge about the data distribution or an unknown process that suddenly …
Follow the trail: Machine learning for fraud detection in Fintech applications
B Stojanović, J Božić, K Hofer-Schmitz, K Nahrgang… - Sensors, 2021 - mdpi.com
Financial technology, or Fintech, represents an emerging industry on the global market. With
online transactions on the rise, the use of IT for automation of financial services is of …
online transactions on the rise, the use of IT for automation of financial services is of …
DeepFMD: computational analysis for malaria detection in blood-smear images using deep-learning features
Malaria is one of the most infectious diseases in the world, particularly in developing
continents such as Africa and Asia. Due to the high number of cases and lack of sufficient …
continents such as Africa and Asia. Due to the high number of cases and lack of sufficient …
Oppositional Cat Swarm Optimization‐Based Feature Selection Approach for Credit Card Fraud Detection
N Prabhakaran, R Nedunchelian - Computational Intelligence …, 2023 - Wiley Online Library
Credit card fraud has drastically increased in recent times due to the advancements in e‐
commerce systems and communication technology. Falsified credit card transactions affect …
commerce systems and communication technology. Falsified credit card transactions affect …