11 citations · 12 across the 6 of their papers we have counts for
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cs.CR2024
CAMH: Advancing Model Hijacking Attack in Machine Learning
Xing He, Jiahao Chen, Yuwen Pu +5
In the burgeoning domain of machine learning, the reliance on third-party services for model training and the adoption of pre-trained models have surged. However, this reliance int…
cs.CR2024
Enhancing Adversarial Transferability with Adversarial Weight Tuning
Jiahao Chen, Zhou Feng, Rui Zeng +6
Deep neural networks (DNNs) are vulnerable to adversarial examples (AEs) that mislead the model while appearing benign to human observers. A critical concern is the transferability…
cs.CR2023★ 1 cited
MEAOD: Model Extraction Attack against Object Detectors
Zeyu Li, Chenghui Shi, Yuwen Pu +4
The widespread use of deep learning technology across various industries has made deep neural network models highly valuable and, as a result, attractive targets for potential atta…