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20182025
most citedTowards Good Practices in Evaluating Transfer Adversarial Attacks

7 citations · 35 across the 15 of their papers we have counts for

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Showing 2022Show all

5 papers · 1 filter

cs.LG2022★ 1 cited

Generative Poisoning Using Random Discriminators

Dirren van Vlijmen, Alex Kolmus, Zhuoran Liu +2

We introduce ShortcutGen, a new data poisoning attack that generates sample-dependent, error-minimizing perturbations by learning a generator. The key novelty of ShortcutGen is the…

cs.CR2022★ 7 cited

Towards Good Practices in Evaluating Transfer Adversarial Attacks

Zhengyu Zhao, Hanwei Zhang, Renjue Li +3

Transfer adversarial attacks raise critical security concerns in real-world, black-box scenarios. However, the actual progress of this field is difficult to assess due to two commo…

cs.CR2022

Membership Inference Attacks by Exploiting Loss Trajectory

Yiyong Liu, Zhengyu Zhao, Michael Backes +1

Machine learning models are vulnerable to membership inference attacks in which an adversary aims to predict whether or not a particular sample was contained in the target model's…

cs.CV2022

The Importance of Image Interpretation: Patterns of Semantic Misclassification in Real-World Adversarial Images

Zhengyu Zhao, Nga Dang, Martha Larson

Adversarial images are created with the intention of causing an image classifier to produce a misclassification. In this paper, we propose that adversarial images should be evaluat…

cs.LG2022

Level Up with ML Vulnerability Identification: Leveraging Domain Constraints in Feature Space for Robust Android Malware Detection

Hamid Bostani, Zhengyu Zhao, Zhuoran Liu +1

Machine Learning (ML) promises to enhance the efficacy of Android Malware Detection (AMD); however, ML models are vulnerable to realistic evasion attacks--crafting realizable Adver…