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Deep neural networks (DNNs) have been found to be vulnerable to backdoor attacks, raising security concerns about their deployment in mission-critical applications.
Imagenet: A large-scale hierarchical image database
Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., and Fei-Fei, L · 2009
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Learning multiple layers of features from tiny images
Krizhevsky, A., Hinton, G., et al · 2009
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Intriguing properties of neural networks
Szegedy, C., Zaremba, W., Sutskever, I., Bruna, J., Erhan, D., Goodfellow, I., and Fergus, R · 2013
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Deep residual learning for image recognition
He, K., Zhang, X., Ren, S., and Sun, J · 2016
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Targeted backdoor attacks on deep learning systems using data poisoning
Chen, X., Liu, C., Li, B., Lu, K., and Song, D · 2017
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Badnets: Identifying vulnerabilities in the machine learning model supply chain
Gu, T., Dolan-Gavitt, B., and Garg, S · 2017
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Poison frogs! targeted clean-label poisoning attacks on neural networks
Shafahi, A., Huang, W. R., Najibi, M., Suciu, O., Studer, C., Dumitras, T., and Goldstein, T · 2018
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Spectral signatures in backdoor attacks
Tran, B., Li, J., and Madry, A · 2018
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A new backdoor attack in cnns by training set corruption without label poisoning
Barni, M., Kallas, K., and Tondi, B · 2019
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Detecting backdoor attacks on deep neural networks by activation clustering
Chen, B., Carvalho, W., Baracaldo, N., Ludwig, H., Edwards, B., Lee, T., Molloy, I., and Srivastava, B · 2019
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Strip: A defence against trojan attacks on deep neural networks
Gao, Y., Xu, C., Wang, D., Chen, S., Ranasinghe, D. C., and Nepal, S · 2019
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Tabor: A highly accurate approach to inspecting and restoring trojan backdoors in ai systems
Guo, W., Wang, L., Xing, X., Du, M., and Song, D · 2019
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Abs: Scanning neural networks for back-doors by artificial brain stimulation
Liu, Y., Lee, W.-C., Tao, G., Ma, S., Aafer, Y., and Zhang, X · 2019
Cited alongside, same era.
Clean-label backdoor attacks
Turner, A., Tsipras, D., and Madry, A · 2019
Cited alongside, same era.
Neural cleanse: Identifying and mitigating backdoor attacks in neural networks
Wang, B., Yao, Y., Shan, S., Li, H., Viswanath, B., Zheng, H., and Zhao, B. Y · 2019
Cited alongside, same era.
Can adversarial weight perturbations inject neural backdoors
Garg, S., Kumar, A., Goel, V., and Liang, Y · 2020
Cited alongside, same era.
Rethinking the trigger of backdoor attack
Li, Y., Zhai, T., Wu, B., Jiang, Y., Li, Z., and Xia, S · 2020
Cited alongside, same era.
Reflection backdoor: A natural backdoor attack on deep neural networks
Adversarial neuron pruning purifies backdoored deep models
Wu, D. and Wang, Y · 2021
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Detecting ai trojans using meta neural analysis
Xu, X., Wang, Q., Li, H., Borisov, N., Gunter, C. A., and Li, B · 2021
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Rethinking the backdoor attacks’ triggers: A frequency perspective
Zeng, Y., Park, W., Mao, Z. M., and Jia, R · 2021
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Effective backdoor defense by exploiting sensitivity of poisoned samples
Chen, W., Wu, B., and Wang, H · 2022
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Few-shot backdoor defense using shapley estimation
Guan, J., Tu, Z., He, R., and Tao, D · 2022
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Trigger hunting with a topological prior for trojan detection
Hu, X., Lin, X., Cogswell, M., Yao, Y., Jha, S., and Chen, C · 2022
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Liu, Y., Ma, X., Bailey, J., and Lu, F · 2020
Cited alongside, same era.
Input-aware dynamic backdoor attack
Nguyen, A. and Tran, A · 2020
Cited alongside, same era.
Deep feature space trojan attack of neural networks by controlled detoxification
Cheng, S., Liu, Y., Ma, S., and Zhang, X · 2021
Cited alongside, same era.
Lira: Learnable, imperceptible and robust backdoor attacks
Doan, K., Lao, Y., Zhao, W., and Li, P · 2021
Cited alongside, same era.
Wanet–imperceptible warping-based backdoor attack
Nguyen, A. and Tran, A · 2021
Cited alongside, same era.
Backdoor scanning for deep neural networks through k-arm optimization
Shen, G., Liu, Y., Tao, G., An, S., Xu, Q., Cheng, S., Ma, S., and Zhang, X · 2021
Cited alongside, same era.
Demon in the variant: Statistical analysis of dnns for robust backdoor contamination detection
Tang, D., Wang, X., Tang, H., and Zhang, K · 2021
Cited alongside, same era.
Backdoor defense via decoupling the training process
Huang, K., Li, Y., Wu, B., Qin, Z., and Ren, K · 2022
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Complex backdoor detection by symmetric feature differencing
Liu, Y., Shen, G., Tao, G., Wang, Z., Ma, S., and Zhang, X · 2022
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Adversarial unlearning of backdoors via implicit hypergradient
Zeng, Y., Chen, S., Park, W., Mao, Z. M., Jin, M., and Jia, R · 2022
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Defeat: Deep hidden feature backdoor attacks by imperceptible perturbation and latent representation constraints
Zhao, Z., Chen, X., Xuan, Y., Dong, Y., Wang, D., and Liang, K · 2022
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Data-free backdoor removal based on channel lipschitzness
Zheng, R., Tang, R., Li, J., and Liu, L · 2022
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