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Extensive evidence has demonstrated that deep neural networks (DNNs) are vulnerable to backdoor attacks, which motivates the development of backdoor attacks detection.
Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition
Johannes Stallkamp, Marc Schlipsing, Jan Salmen, and Christian Igel · 2012
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Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus · 2013
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Explaining and harnessing adversarial examples
Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy · 2014
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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Tiny imagenet visual recognition challenge
Ya Le and Xuan Yang · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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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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Badnets: Identifying vulnerabilities in the machine learning model supply chain
Tianyu Gu, Brendan Dolan-Gavitt, and Siddharth Garg · 2017
Earlier work this paper cites.
Densely connected convolutional networks
Gao Huang, Zhuang Liu, Laurens Van Der Maaten, and Kilian Q Weinberger · 2017
Earlier work this paper cites.
Trojaning attack on neural networks
Yingqi Liu, Shiqing Ma, Yousra Aafer, Wen-Chuan Lee, Juan Zhai, Weihang Wang, and Xiangyu Zhang · 2017
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Towards deep learning models resistant to adversarial attacks
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu · 2017
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Grad-cam: Visual explanations from deep networks via gradient-based localization
Ramprasaath R Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra · 2017
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Cited alongside, same era.
Adversarial examples in the physical world
Alexey Kurakin, Ian J Goodfellow, and Samy Bengio · 2018
Cited alongside, same era.
Mobilenetv2: Inverted residuals and linear bottlenecks
Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, and Liang-Chieh Chen · 2018
Cited alongside, same era.
Spectral signatures in backdoor attacks
Brandon Tran, Jerry Li, and Aleksander Madry · 2018
Cited alongside, same era.
A new backdoor attack in cnns by training set corruption without label poisoning
Universal litmus patterns: Revealing backdoor attacks in cnns
Soheil Kolouri, Aniruddha Saha, Hamed Pirsiavash, and Heiko Hoffmann · 2020
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Spatiotemporal attacks for embodied agents
Aishan Liu, Tairan Huang, Xianglong Liu, Yitao Xu, Yuqing Ma, Xinyun Chen, Stephen J Maybank, and Dacheng Tao · 2020
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Input-aware dynamic backdoor attack
Tuan Anh Nguyen and Anh Tran · 2020
Later among the works it cites.
Hidden trigger backdoor attacks
Aniruddha Saha, Akshayvarun Subramanya, and Hamed Pirsiavash · 2020
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Practical detection of trojan neural networks: Data-limited and data-free cases
Ren Wang, Gaoyuan Zhang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong, and Meng Wang · 2020
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Clean-label backdoor attacks on video recognition models
Shihao Zhao, Xingjun Ma, Xiang Zheng, James Bailey, Jingjing Chen, and Yu-Gang Jiang · 2020
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Mauro Barni, Kassem Kallas, and Benedetta Tondi · 2019
Cited alongside, same era.
Strip: A defence against trojan attacks on deep neural networks
Yansong Gao, Change Xu, Derui Wang, Shiping Chen, Damith C Ranasinghe, and Surya Nepal · 2019
Cited alongside, same era.
Perceptual-sensitive gan for generating adversarial patches
Aishan Liu, Xianglong Liu, Jiaxin Fan, Yuqing Ma, Anlan Zhang, Huiyuan Xie, and Dacheng Tao · 2019
Cited alongside, same era.
Defending neural backdoors via generative distribution modeling
Ximing Qiao, Yukun Yang, and Hai Li · 2019
Cited alongside, same era.
Label-consistent backdoor attacks
Alexander Turner, Dimitris Tsipras, and Aleksander Madry · 2019
Cited alongside, same era.
Neural cleanse: Identifying and mitigating backdoor attacks in neural networks
Bolun Wang, Yuanshun Yao, Shawn Shan, Huiying Li, Bimal Viswanath, Haitao Zheng, and Ben Y Zhao · 2019
Cited alongside, same era.
Sentinet: Detecting localized universal attacks against deep learning systems
Edward Chou, Florian Tramer, and Giancarlo Pellegrino · 2020
Cited alongside, same era.
Later among the works it cites.
Gangsweep: Sweep out neural backdoors by gan
Liuwan Zhu, Rui Ning, Cong Wang, Chunsheng Xin, and Hongyi Wu · 2020
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Aeva: Black-box backdoor detection using adversarial extreme value analysis
Junfeng Guo, Ang Li, and Cong Liu · 2021
Later among the works it cites.
Wanet–imperceptible warping-based backdoor attack
Anh Nguyen and Anh Tran · 2021
Later among the works it cites.
Detecting ai trojans using meta neural analysis
Xiaojun Xu, Qi Wang, Huichen Li, Nikita Borisov, Carl A Gunter, and Bo Li · 2021
Later among the works it cites.
Adversarial fine-tuning for backdoor defense: Connect adversarial examples to triggered samples
Bingxu Mu, Le Wang, and Zhenxing Niu · 2022
Closest in time.
Universal post-training backdoor detection
Hang Wang, Zhen Xiang, David J Miller, and George Kesidis · 2022
Closest in time.