Robust Assessment of Real-World Adversarial Examples

Brett Jefferson; Carlos Ortiz Marrero

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arXiv · 1911.10435

Robust Assessment of Real-World Adversarial Examples

Brett Jefferson·Carlos Ortiz Marrero

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Abstract

We explore rigorous, systematic, and controlled experimental evaluation of adversarial examples in the real world and propose a testing regimen for evaluation of real world adversarial objects. We show that for small scene/ environmental perturbations, large adversarial performance differences exist. Current state of adversarial reporting exists largely as a frequency count over a dynamic collections of scenes. Our work underscores the need for either a more complete report or a score that incorporates scene changes and baseline performance for models and environments tested by adversarial developers. We put forth a score that attempts to address the above issues in a straight-forward exemplar application for multiple generated adversary examples. We contribute the following: 1. a testbed for adversarial assessment, 2. a score for adversarial examples, and 3. a collection of additional evaluations on testbed data.

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BibTeX RIS

Brett Jefferson, Carlos Ortiz Marrero. 2020-03-15. Robust Assessment of Real-World Adversarial Examples. https://arxiv.org/abs/1911.10435

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