preprintarXiv (Cornell University)Feb 18, 2019GREEN OA

On Evaluating Adversarial Robustness

Indexed inarxivdatacite

Abstract

Correctly evaluating defenses against adversarial examples has proven to be extremely difficult. Despite the significant amount of recent work attempting to design defenses that withstand adaptive attacks, few have succeeded; most papers that propose defenses are quickly shown to be incorrect. We believe a large contributing factor is the difficulty of performing security evaluations. In this paper, we discuss the methodological foundations, review commonly accepted best practices, and suggest new methods for evaluating defenses to adversarial examples. We hope that both researchers developing defenses as well as readers and reviewers who wish to understand the completeness of an evaluation consider our advice…

Citation impact

581
total citations
FWCI
Percentile
References
73
Citations per year

Authors

9

Topics & keywords

Keywords
  • Adversarial system
  • Robustness (evolution)
  • Computer science
  • Artificial intelligence
No related works found for this paper.