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STROKE: Simple Sparse Structural Occlusions for Black-Box Adversarial Attacks
Ankit Gupta, Akshat Pandya, Paul Lin, Christoph Adami, Emily Dolson

STROKE: Simple Sparse Structural Occlusions for Black-Box Adversarial Attacks

Computer Science & Mathematics Published 2026 Verification Pending

Overview & Synopsis

We introduce STROKE, a query-efficient score-based black-box adversarial attack that constructs perturbations from simple oriented rectangular occlusions. STROKE optimizes these perturbations through a lightweight greedy add-and-refine procedure. Across diverse image classifiers, STROKE achieves high attack success with low query counts at nominal 1--2\% area settings, showing favorable performance relative to existing patch-based attacks in several configurations. Matched comparisons further demonstrate substantial reductions in wall-clock attack time, while ablation studies examine the key design choices and effectiveness across structural primitives. These findings suggest that simple structural occlusions offer an effective and computationally efficient search space for black-box adversarial attacks.

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Indexed from repository: arXiv (arxiv.org)
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Document Information

Document Title STROKE: Simple Sparse Structural Occlusions for Black-Box Adversarial Attacks
Author / Organization Ankit Gupta, Akshat Pandya, Paul Lin, Christoph Adami, Emily Dolson
Subject & Discipline cs.CV
Categories Computer Science & Mathematics
Publication Year 2026
License / Rights arXiv Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website arXiv (arxiv.org)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-118346
Original Source Link Visit Source Page on arxiv.org »