Edward Raff

Adversarial Machine Learning Attacks on Financial Reporting via Maximum Violated Multi-Objective Attack (video, pdf)

Speaker: Edward Raff

Author(s): Edward Raff; Karen Kukla; Michel Benaroch; Joseph Comprix

Abstract: This work explores Adversarial Machine Learning (AML) attacks on financial reporting, demonstrating how bad actors can manipulate financial statements to inflate earnings and reduce fraud scores simultaneously, highlighting a critical information security vulnerability in financial systems.