Adversarial attacks and defenses in machine learning and deep neural network (DNN) have
been gaining significant attention due to the rapidly growing applications of deep learning in …

Significant research has been carried out in the field of User Behavior Analysis, focused on
understanding, modeling and predicting past, present and future behaviors of users …

Fraud detection systems support advanced detection techniques based on complex rules,
statistical modelling and machine learning. However, alerts triggered by these systems still …

Financial services are used everywhere and function with high complexity. With the increase
in online transacting, frauds too are increasing alarmingly. An automated Fraud Detection …

Specialty literature and solutions in the market have been focusing in the last decade on
collecting and aggregating significant amounts of data about transactions (and user …

The effectiveness of transaction fraud detection methods directly affects the loss of users in
online transactions. However, for low-frequency users with small transaction volume, the …

Internet consumer credit services are defined as the provision of consumer credit services
through internet platforms. While these services have benefited the public, they also present …

In the digital era, security issue during online shop** is one of the prominent areas of the
research for both the sides users and a businessman. In the current scenario, text-based …

The digital era has seen a marked increase in financial fraud. edge ML emerged as a
promising solution for smartphone payment services fraud detection, enabling the …

Behavior analysis has been used widely in antifraud transactions. However, existing
methods of behavior analysis mainly focus on behavior patterns and do not fully consider …