Detection of AI Deepfake and Fraud in Online Payments Using GAN-Based Models
PositiveArtificial Intelligence
- A recent study has introduced a Generative Adversarial Network (GAN)-based model aimed at detecting AI deepfakes and fraudulent activities in online payment systems. This model is trained on a dataset of real-world payment images and deepfake images, achieving a detection accuracy exceeding 95%. The research highlights the growing challenge of identifying sophisticated fraud methods that traditional security systems struggle to address.
- The development of this GAN-based model is significant for enhancing digital security in financial services, particularly as online transactions become increasingly susceptible to manipulation through deepfake technology. By accurately distinguishing between legitimate and fraudulent transactions, this model could bolster consumer trust and reduce financial losses associated with fraud.
- This advancement in AI-driven detection methods reflects a broader trend in the application of generative models across various domains, including healthcare and environmental monitoring. While the potential of generative AI is being harnessed for positive applications, concerns regarding ethical regulations and privacy implications persist, underscoring the need for responsible innovation in AI technologies.
— via World Pulse Now AI Editorial System
