Credit Card Fraud Detection Using GASF

Credit card fraud detection is an emerging challenging problem due to the changing techniques used by fraudsters and the large number of transactions. By evaluating the complexity and scale of fraud detection, traditional methods of fraud detection often involve manual processing, which can lead to delays in detecting and identifying new attack strategies. The GASF technique is a visualization approach that not only reduces the time required for data processing, but also provides a more visual and effective way to detect fraud. GASF has shown how transaction history pattern can be visualized effectively based on encoding the temporal relationship between transactions. The GASF approach, which focuses on understanding temporal dynamics, can significantly enhance the security of financial systems. The model performs well and shows 96 percentage of accuracy.