Decision-based adversarial attack with frequency mixup | |
Xiu-Chuan Li; Xu-Yao Zhang; Fei Yin; Cheng-Lin Liu | |
刊名 | IEEE Trans. Information Forensics and Security (TIFS) |
2022-03 | |
期号 | 17页码:1038-1052 |
关键词 | Decision-based attack , detection , frequency domain |
英文摘要 | It has been widely observed that deep neural networks are highly vulnerable to adversarial examples. Decision-based attacks could generate adversarial examples based solely on top-1 labels returned by the target model. However, they typically make excessive queries and could not bypass detection effectively. To comprehensively assess a decision-based attack, besides its query efficiency, the performance against detection is also a concern. Considering that previous detections consume massive resources and always mistakenly recognize benign video frames as malicious attacks, we design a lightweight detection called boundary detection to overcome the above limitations, whose success reveals serious limitations of existing decision-based attacks. To develop more powerful attacks, we first present f-mixup as a basic method to produce candidate adversarial examples in the frequency domain. Using f-mixup as the building block, we propose f-attack as a complete decision-based attack. With the help of several natural images, f-attack could both work well with limited (hundreds of) queries and bypass detection effectively. Nevertheless, if the attacker could make relatively adequate (thousands of) queries and the target model is not equipped with detection, f-attack will lag behind existing decision-based attacks. We additionally introduce frequency binary search based on f-mixup , which serves as a plug-and-play module for existing decision-based attacks to further improve their query efficiency. Experimental results verify the effectiveness of our proposed methods. |
内容类型 | 期刊论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/47473] |
专题 | 自动化研究所_模式识别国家重点实验室_模式分析与学习团队 |
通讯作者 | Xu-Yao Zhang |
作者单位 | 中科院自动化所 |
推荐引用方式 GB/T 7714 | Xiu-Chuan Li,Xu-Yao Zhang,Fei Yin,et al. Decision-based adversarial attack with frequency mixup[J]. IEEE Trans. Information Forensics and Security (TIFS),2022(17):1038-1052. |
APA | Xiu-Chuan Li,Xu-Yao Zhang,Fei Yin,&Cheng-Lin Liu.(2022).Decision-based adversarial attack with frequency mixup.IEEE Trans. Information Forensics and Security (TIFS)(17),1038-1052. |
MLA | Xiu-Chuan Li,et al."Decision-based adversarial attack with frequency mixup".IEEE Trans. Information Forensics and Security (TIFS) .17(2022):1038-1052. |
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