Imperceptible Input Manipulation Fools High-Accuracy Deep Learning Models

Executive Summary

Deep learning models with strong predictive performance can be deceived by minute, humanly invisible alterations to input data, producing entirely wrong outputs. Boards must recognise that conventional accuracy benchmarks provide no assurance against deliberate adversarial manipulation in deployed systems.