Fraud-RLA: A Reinforcement Learning Adversarial Attack Against Credit Card Fraud Detection

Summary

Fraud-RLA is a new adversarial attack against credit card fraud detection systems that uses reinforcement learning to evade detection. It aims to maximize the amount stolen while requiring substantially less prior knowledge than competing methods. The authors report that it remains effective on a realistic fraud detection system under the constraints of their threat model.

Topics

• Adversarial machine learning

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