Summary of Watertox: the Art Of Simplicity in Universal Attacks a Cross-model Framework For Robust Adversarial Generation, by Zhenghao Gao et al.
Watertox: The Art of Simplicity in Universal Attacks A Cross-Model Framework for Robust Adversarial Generation
by Zhenghao Gao, Shengjie Xu, Meixi Chen, Fangyao Zhao
First submitted to arxiv on: 20 Dec 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Cryptography and Security (cs.CR)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper presents Watertox, an innovative adversarial attack framework that demonstrates remarkable effectiveness through architectural diversity and precision-controlled perturbations. By combining uniform baseline perturbations and targeted enhancements, the framework achieves significant model accuracy reductions against state-of-the-art architectures. The authors leverage an ensemble of complementary architectures, including VGG and ConvNeXt, to synthesize diverse perspectives using an innovative voting mechanism. Watertox reduces model accuracy from 70.6% to 16.0%, with zero-shot attacks achieving up to 98.8% accuracy reduction against unseen architectures. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper introduces a new type of attack called Watertox that is very good at making models less accurate. It does this by using different types of computer vision architectures and combining their results in a special way. This helps the attack work well even if it’s never seen the model before. The attack makes the model much worse, reducing its accuracy from 70% to just 16%. This is an important advancement that could be used to make computer systems more secure. |
Keywords
» Artificial intelligence » Precision » Zero shot
