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Recently, a special type of data poisoning (DP) attack targeting Deep Neural Network (DNN) classifiers, known as a backdoor, was proposed.
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Cited alongside, same era.
Stealing machine learning models via prediction apis
F. Tamer, F. Zhang, A. Juels, M. Reiter, and T. Ristenpart · 2016
Cited alongside, same era.
Targeted backdoor attacks on deep learning systems using data poisoning
X. Chen, C. Liu, B. Li, K. Lu, and D. Song · 2017
Cited alongside, same era.
Universal adversarial perturbations
S. Mooosavi-Dezfooli, A. Fawzi, O. Fawzi, and P. Frossard · 2017
Cited alongside, same era.
Practical black box attacks against machine learning
N. Papernot, P. McDaniel, I. Goodfellow, S. Jha, Z. Celik, and A. Swami · 2017
Cited alongside, same era.
Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering
BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain
T. Gu, B. Dolan-Gavitt, and S. Garg · 2019
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TABOR: A Highly Accurate Approach to Inspecting and Restoring Trojan Backdoors in AI Systems
W. Guo, L. Wang, X. Xing, M. Du, and D. Song · 2019
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When Not to Classify: Anomaly Detection of Attacks (ADA) on DNN classifiers at test time
D.J. Miller, Y. Wang, and G. Kesidis · 2019
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D.J. Miller, Z. Xiang, and G. Kesidis · 2019
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Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural Networks
B. Wang, Y. Yao, S. Shan, H. Li, B. Viswanath, H. Zheng, and B.Y. Zhao · 2019
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B. Chen, W. Carvalho, N. Baracaldo, H. Ludwig, B. Edwards, T. Lee, I. Molloy, and B. Srivastava · 2018
Cited alongside, same era.
Backdoor embedding in convolutional neural network models via invisible perturbation
C. Liao, H. Zhong, A. Squicciarini, S. Zhu, and D.J. Miller · 2018
Cited alongside, same era.
Fine-Pruning: Defending Against Backdoor Attacks on Deep Neural Networks
K. Liu, B. Doan-Gavitt, and S. Garg · 2018
Cited alongside, same era.
Trojaning attack on neural networks
Y. Liu, S. Ma, Y. Aafer, W.-C. Lee, and Zhai J · 2018
Cited alongside, same era.
Spectral signatures in backdoor attacks
B. Tran, J. Li, and A. Madry · 2018
Cited alongside, same era.
A backdoor attack against lstm-based text classification systems
J. Dai and C. Chen · 2019
Cited alongside, same era.
https://www.iarpa.gov/index.php/research-programs/trojai
Trojans in artificial intelligence (TrojAI)
Cited in the paper.
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When Not to Classify: Detection of Reverse Engineering Attacks on DNN Image Classifiers
Y. Wang, D.J. Miller, and G. Kesidis · 2019
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A Benchmark Study of Backdoor Data Poisoning Defenses for Deep Neural Network Classifiers and A Novel Defense Only Legitimate Samples
Z. Xiang, D.J. Miller, and G. Kesidis · 2019
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Adversarial examples: Attacks and defenses for deep learning
X. Yuan, P. He, Q. Zhu, and X. Li · 2019
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Hidden trigger backdoor attacks
H. Pirsiavash A. Saha, A. Subramanya · 2020
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Revealing backdoors, post-training, in dnn classifiers via novel inference on optimized perturbations inducing group misclassification
Z. Xiang, D. J. Miller, and G. Kesidis · 2020
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Revealing Perceptible Backdoors, without the Training Set, via the Maximum Achievable Misclassification Fraction Statistic
Z. Xiang, D. J. Miller, and G. Kesidis · 2020
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