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02/23/2023
Investigating Catastrophic Overfitting in Fast Adversarial Training: A Self-fitting Perspective
Although fast adversarial training provides an efficient approach for bu...
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11/22/2022
Self-Ensemble Protection: Training Checkpoints Are Good Data Protectors
As data become increasingly vital for deep learning, a company would be ...
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08/12/2022
Unifying Gradients to Improve Real-world Robustness for Deep Networks
The wide application of deep neural networks (DNNs) demands an increasin...
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05/24/2022
One-Pixel Shortcut: on the Learning Preference of Deep Neural Networks
Unlearnable examples (ULEs) aim to protect data from unauthorized usage ...
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05/24/2022
Adversarial Attack on Attackers: Post-Process to Mitigate Black-Box Score-Based Query Attacks
The score-based query attacks (SQAs) pose practical threats to deep neur...
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11/24/2021
Subspace Adversarial Training
Single-step adversarial training (AT) has received wide attention as it ...
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05/31/2021
Dominant Patterns: Critical Features Hidden in Deep Neural Networks
In this paper, we find the existence of critical features hidden in Deep...
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05/31/2021
QueryNet: An Efficient Attack Framework with Surrogates Carrying Multiple Identities
Deep Neural Networks (DNNs) are acknowledged as vulnerable to adversaria...
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02/20/2021
Going Far Boosts Attack Transferability, but Do Not Do It
Deep Neural Networks (DNNs) could be easily fooled by Adversarial Exampl...
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08/16/2020
Attack on Multi-Node Attention for Object Detection
This paper focuses on high-transferable adversarial attacks on detection...
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03/04/2020
Double Backpropagation for Training Autoencoders against Adversarial Attack
Deep learning, as widely known, is vulnerable to adversarial samples. Th...
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03/04/2020
Type I Attack for Generative Models
Generative models are popular tools with a wide range of applications. N...
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01/21/2020
Generate High-Resolution Adversarial Samples by Identifying Effective Features
As the prevalence of deep learning in computer vision, adversarial sampl...
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01/16/2020
Universal Adversarial Attack on Attention and the Resulting Dataset DAmageNet
Adversarial attacks on deep neural networks (DNNs) have been found for s...
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12/16/2019