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Third-party resources ($e.g.$, samples, backbones, and pre-trained models) are usually involved in the training of deep neural networks (DNNs), which brings backdoor attacks as a new training-phase threat.
Deep learning
Yann LeCun, Yoshua Bengio, and Geoffrey Hinton · 2015
Earlier work this paper cites.
Learning compact feature descriptor and adaptive matching framework for face recognition
Zhifeng Li, Dihong Gong, Xuelong Li, and Dacheng Tao · 2015
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Targeted backdoor attacks on deep learning systems using data poisoning
Xinyun Chen, Chang Liu, Bo Li, Kimberly Lu, and Dawn Song · 2017
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Neural trojans
Yuntao Liu, Yang Xie, and Ankur Srivastava · 2017
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Fine-pruning: Defending against backdooring attacks on deep neural networks
Kang Liu, Brendan Dolan-Gavitt, and Siddharth Garg · 2018
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Spectral signatures in backdoor attacks
Brandon Tran, Jerry Li, and Aleksander Madry · 2018
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Badnets: Evaluating backdooring attacks on deep neural networks
Tianyu Gu, Kang Liu, Brendan Dolan-Gavitt, and Siddharth Garg · 2019
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Label-consistent backdoor attacks
Alexander Turner, Dimitris Tsipras, and Aleksander Madry · 2019
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Robust anomaly detection and backdoor attack detection via differential privacy
Min Du, Ruoxi Jia, and Dawn Song · 2020
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Backdoor attacks and countermeasures on deep learning: A comprehensive review
Yansong Gao, Bao Gia Doan, Zhi Zhang, Siqi Ma, Jiliang Zhang, Anmin Fu, Surya Nepal, and Hyoungshick Kim · 2020
Earlier work this paper cites.
Composite backdoor attack for deep neural network by mixing existing benign features
Junyu Lin, Lei Xu, Yingqi Liu, and Xiangyu Zhang · 2020
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Reflection backdoor: A natural backdoor attack on deep neural networks
Yunfei Liu, Xingjun Ma, James Bailey, and Feng Lu · 2020
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Input-aware dynamic backdoor attack
Anh Nguyen and Anh Tran · 2020
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Certified robustness to label-flipping attacks via randomized smoothing
Elan Rosenfeld, Ezra Winston, Pradeep Ravikumar, and J. Zico Kolter · 2020
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An embarrassingly simple approach for trojan attack in deep neural networks
Ruixiang Tang, Mengnan Du, Ninghao Liu, Fan Yang, and Xia Hu · 2020
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Automatic perturbation analysis for scalable certified robustness and beyond
Kaidi Xu, Zhouxing Shi, Huan Zhang, Yihan Wang, Kai-Wei Chang, Minlie Huang, Bhavya Kailkhura, Xue Lin, and Cho-Jui Hsieh · 2020
Cited alongside, same era.
Blind backdoors in deep learning models
Eugene Bagdasaryan and Vitaly Shmatikov · 2021
Cited alongside, same era.
Strong data augmentation sanitizes poisoning and backdoor attacks without an accuracy tradeoff
Eitan Borgnia, Valeriia Cherepanova, Liam Fowl, Amin Ghiasi, Jonas Geiping, Micah Goldblum, Tom Goldstein, and Arjun Gupta · 2021
Cited alongside, same era.
Deep feature space trojan attack of neural networks by controlled detoxification
Siyuan Cheng, Yingqi Liu, Shiqing Ma, and Xiangyu Zhang · 2021
Cited alongside, same era.
Lira: Learnable, imperceptible and robust backdoor attacks
Khoa Doan, Yingjie Lao, Weijie Zhao, and Ping Li · 2021
Cited alongside, same era.
Backdoor defense via decoupling the training process
Kunzhe Huang, Yiming Li, Baoyuan Wu, Zhan Qin, and Kui Ren · 2022
Later among the works it cites.
Certified robustness of nearest neighbors against data poisoning and backdoor attacks
Jinyuan Jia, Yupei Liu, Xiaoyu Cao, and Neil Zhenqiang Gong · 2022
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Trojanzoo: Towards unified, holistic, and practical evaluation of neural backdoors
Ren Pang, Zheng Zhang, Xiangshan Gao, Zhaohan Xi, Shouling Ji, Peng Cheng, Xiapu Luo, and Ting Wang · 2022
Later among the works it cites.
Towards practical deployment-stage backdoor attack on deep neural networks
Xiangyu Qi, Tinghao Xie, Ruizhe Pan, Jifeng Zhu, Yong Yang, and Kai Bu · 2022
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Sleeper agent: Scalable hidden trigger backdoors for neural networks trained from scratch
Hossein Souri, Micah Goldblum, Liam Fowl, Rama Chellappa, and Tom Goldstein · 2022
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Yansong Gao, Yeonjae Kim, Bao Gia Doan, Zhi Zhang, Gongxuan Zhang, Surya Nepal, Damith Ranasinghe, and Hyoungshick Kim · 2021
Cited alongside, same era.
Wanet-imperceptible warping-based backdoor attack
Tuan Anh Nguyen and Anh Tuan Tran · 2021
Cited alongside, same era.
Backdoor scanning for deep neural networks through k-arm optimization
Guangyu Shen, Yingqi Liu, Guanhong Tao, Shengwei An, Qiuling Xu, Siyuan Cheng, Shiqing Ma, and Xiangyu Zhang · 2021
Cited alongside, same era.
Adversarial neuron pruning purifies backdoored deep models
Dongxian Wu and Yisen Wang · 2021
Cited alongside, same era.
A backdoor attack against 3d point cloud classifiers
Zhen Xiang, David J Miller, Siheng Chen, Xi Li, and George Kesidis · 2021
Cited alongside, same era.
Rethinking the backdoor attacks’ triggers: A frequency perspective
Yi Zeng, Won Park, Z Morley Mao, and Ruoxi Jia · 2021
Cited alongside, same era.
Backdoor attack against speaker verification
Tongqing Zhai, Yiming Li, Ziqi Zhang, Baoyuan Wu, Yong Jiang, and Shu-Tao Xia · 2021
Cited alongside, same era.
Better trigger inversion optimization in backdoor scanning
Guanhong Tao, Guangyu Shen, Yingqi Liu, Shengwei An, Qiuling Xu, Shiqing Ma, Pan Li, and Xiangyu Zhang · 2022
Later among the works it cites.
Training with more confidence: Mitigating injected and natural backdoors during training
Zhenting Wang, Hailun Ding, Juan Zhai, and Shiqing Ma · 2022
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Rab: Provable robustness against backdoor attacks
Maurice Weber, Xiaojun Xu, Bojan Karlaš, Ce Zhang, and Bo Li · 2022
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Backdoorbench: A comprehensive benchmark of backdoor learning
Baoyuan Wu, Hongrui Chen, Mingda Zhang, Zihao Zhu, Shaokui Wei, Danni Yuan, and Chao Shen · 2022
Later among the works it cites.
Post-training detection of backdoor attacks for two-class and multi-attack scenarios
Zhen Xiang, David J Miller, and George Kesidis · 2022
Later among the works it cites.
Adversarial unlearning of backdoors via implicit hypergradient
Yi Zeng, Si Chen, Won Park Z. Morley Mao, Ming Jin, and Ruoxi Jia · 2022
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Zhendong Zhao, Xiaojun Chen, Yuexin Xuan, Ye Dong, Dakui Wang, and Kaitai Liang · 2022
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Scale-up: An efficient black-box input-level backdoor detection via analyzing scaled prediction consistency
Junfeng Guo, Yiming Li, Xun Chen, Hanqing Guo, Lichao Sun, and Cong Liu · 2023
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Revisiting the assumption of latent separability for backdoor defenses
Xiangyu Qi, Tinghao Xie, Yiming Li, Saeed Mahloujifar, and Prateek Mittal · 2023
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Towards robustness certification against universal perturbations
Yi Zeng, Zhouxing Shi, Ming Jin, Feiyang Kang, Lingjuan Lyu, Cho-Jui Hsieh, and Ruoxi Jia · 2023
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