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Back-door attack poses a severe threat to deep learning systems.
Learning from delayed rewards
Watkins, C. J. C. H · 1989
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Using confidence bounds for exploitation-exploration trade-offs
Auer, P · 2002
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Finite-time analysis of the multiarmed bandit problem
Auer, P., Cesa-Bianchi, N., and Fischer, P · 2002
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On certifying robustness against backdoor attacks via randomized smoothing
Wang, B., Cao, X., Gong, N. Z., et al · 2002
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An introduction to roc analysis
Fawcett, T · 2006
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Li, S., Ma, S., Xue, M., and Zhao, B. Z. H · 2007
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Li, Y., Wu, B., Jiang, Y., Li, Z., and Xia, S.-T · 2007
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Practical detection of trojan neural networks: Data-limited and data-free cases
Wang, R., Zhang, G., Liu, S., Chen, P.-Y., Xiong, J., and Wang, M · 2007
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Machine learning: a probabilistic perspective
Murphy, K. P · 2012
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Adam: A method for stochastic optimization
Kingma, D. P. and Ba, J · 2014
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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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Neural trojans
Liu, Y., Xie, Y., and Srivastava, A · 2017
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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 · 2018
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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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With great training comes great vulnerability: Practical attacks against transfer learning
Wang, B., Yao, Y., Viswanath, B., Zheng, H., and Zhao, B. Y · 2018
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Poison as a cure: Detecting & neutralizing variable-sized backdoor attacks in deep neural networks
Chan, A. and Ong, Y.-S · 2019
Cited alongside, same era.
Robust anomaly detection and backdoor attack detection via differential privacy
Du, M., Jia, R., and Song, D · 2019
Cited alongside, same era.
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
Cited alongside, same era.
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
Cited alongside, same era.
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
How to backdoor federated learning
Bagdasaryan, E., Veit, A., Hua, Y., Estrin, D., and Shmatikov, V · 2020
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Badnl: Backdoor attacks against nlp models
Chen, X., Salem, A., Backes, M., Ma, S., and Zhang, Y · 2020
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Deep feature space trojan attack of neural networks by controlled detoxification
Cheng, S., Liu, Y., Ma, S., and Zhang, X · 2020
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Sentinet: Detecting localized universal attacks against deep learning systems
Chou, E., Tramèr, F., and Pellegrino, G · 2020
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One-pixel signature: Characterizing cnn models for backdoor detection
Huang, S., Peng, W., Jia, Z., and Tu, Z · 2020
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Cited alongside, same era.
Nic: Detecting adversarial samples with neural network invariant checking
Ma, S. and Liu, Y · 2019
Cited alongside, same era.
Defending neural backdoors via generative distribution modeling
Qiao, X., Yang, Y., and Li, H · 2019
Cited alongside, same era.
Bit-flip attack: Crushing neural network with progressive bit search
Rakin, A. S., He, Z., and Fan, D · 2019
Cited alongside, same era.
A target-agnostic attack on deep models: Exploiting security vulnerabilities of transfer learning
Rezaei, S. and Liu, X · 2019
Cited alongside, same era.
Label-consistent 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.
Dba: Distributed backdoor attacks against federated learning
Xie, C., Huang, K., Chen, P.-Y., and Li, B · 2019
Cited alongside, same era.
Trojai competition
IARPA · 2020
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Universal litmus patterns: Revealing backdoor attacks in cnns
Kolouri, S., Saha, A., Pirsiavash, H., and Hoffmann, H · 2020
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Composite backdoor attack for deep neural network by mixing existing benign features
Lin, J., Xu, L., Liu, Y., and Zhang, X · 2020
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Input-aware dynamic backdoor attack
Nguyen, A. and Tran, A · 2020
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Tbt: Targeted neural network attack with bit trojan
Rakin, A. S., He, Z., and Fan, D · 2020
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Hidden trigger backdoor attacks
Saha, A., Subramanya, A., and Pirsiavash, H · 2020
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Dynamic backdoor attacks against machine learning models
Salem, A., Wen, R., Backes, M., Ma, S., and Zhang, Y · 2020
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Natural backdoor attack on text data
Sun, L · 2020
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Cassandra: Detecting trojaned networks from adversarial perturbations
Zhang, X., Mian, A., Gupta, R., Rahnavard, N., and Shah, M · 2020
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Clean-label backdoor attacks on video recognition models
Zhao, S., Ma, X., Zheng, X., Bailey, J., Chen, J., and Jiang, Y.-G · 2020
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