Beware the Black-Box: on the Robustness of Recent Defenses to Adversarial Examples

TL;DR

This paper evaluates the robustness of recent neural network defenses against adaptive black-box adversarial attacks, revealing most defenses offer only marginal security improvements and emphasizing the need for comprehensive white-box and black-box testing.

Contribution

It provides the first large-scale analysis of nine recent defenses against adaptive black-box attacks, highlighting their limited effectiveness and advocating for more thorough robustness evaluations.

Findings

Most defenses offer less than 25% security improvement.

Effectiveness of attacks increases with more data available to adversaries.

White-box and black-box analyses are both essential for true security assessment.

Abstract

Many defenses have recently been proposed at venues like NIPS, ICML, ICLR and CVPR. These defenses are mainly focused on mitigating white-box attacks. They do not properly examine black-box attacks. In this paper, we expand upon the analysis of these defenses to include adaptive black-box adversaries. Our evaluation is done on nine defenses including Barrage of Random Transforms, ComDefend, Ensemble Diversity, Feature Distillation, The Odds are Odd, Error Correcting Codes, Distribution Classifier Defense, K-Winner Take All and Buffer Zones. Our investigation is done using two black-box adversarial models and six widely studied adversarial attacks for CIFAR-10 and Fashion-MNIST datasets. Our analyses show most recent defenses (7 out of 9) provide only marginal improvements in security ($<25\%$), as compared to undefended networks. For every defense, we also show the relationship between the amount of data the adversary has at their disposal, and the effectiveness of adaptive black-box attacks. Overall, our results paint a clear picture: defenses need both thorough white-box and black-box analyses to be considered secure. We provide this large scale study and analyses to motivate the field to move towards the development of more robust black-box defenses.