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Contrastive learning pre-trains an image encoder using a large amount of unlabeled data such that the image encoder can be used as a general-purpose feature extractor for various downstream tasks.
Can machine learning be secure?
Marco Barreno, Blaine Nelson, Russell Sears, Anthony D Joseph, and J Doug Tygar · 2006
Earlier work this paper cites.
Casting out demons: Sanitizing training data for anomaly sensors
Gabriela F Cretu, Angelos Stavrou, Michael E Locasto, Salvatore J Stolfo, and Angelos D Keromytis · 2008
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Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
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The security of machine learning
Marco Barreno, Blaine Nelson, Anthony D Joseph, and J Doug Tygar · 2010
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An analysis of single-layer networks in unsupervised feature learning
Adam Coates, Andrew Ng, and Honglak Lee · 2011
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Poisoning attacks against support vector machines
Battista Biggio, Blaine Nelson, and Pavel Laskov · 2012
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Imagenet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, et al · 2015
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Data poisoning attacks on factorization-based collaborative filtering
Bo Li, Yining Wang, Aarti Singh, and Yevgeniy Vorobeychik · 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
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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 poisoning of deep learning algorithms with back-gradient optimization
Luis Muñoz-González, Battista Biggio, Ambra Demontis, Andrea Paudice, Vasin Wongrassamee, Emil C Lupu, and Fabio Roli · 2017
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Certified defenses for data poisoning attacks
Jacob Steinhardt, Pang Wei Koh, and Percy Liang · 2017
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Fake co-visitation injection attacks to recommender systems
Guolei Yang, Neil Zhenqiang Gong, and Ying Cai · 2017
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Poisoning attacks to graph-based recommender systems
Minghong Fang, Guolei Yang, Neil Zhenqiang Gong, and Jia Liu · 2018
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Stronger data poisoning attacks break data sanitization defenses
Pang Wei Koh, Jacob Steinhardt, and Percy Liang · 2018
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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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Detection of adversarial training examples in poisoning attacks through anomaly detection
Andrea Paudice, Luis Muñoz-González, Andras Gyorgy, and Emil C Lupu · 2018
Earlier work this paper cites.
Label sanitization against label flipping poisoning attacks
Andrea Paudice, Luis Muñoz-González, and Emil C Lupu · 2018
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Poison frogs! targeted clean-label poisoning attacks on neural networks
Ali Shafahi, W Ronny Huang, Mahyar Najibi, Octavian Suciu, Christoph Studer, Tudor Dumitras, and Tom Goldstein · 2018
Cited alongside, same era.
Spectral signatures in backdoor attacks
Brandon Tran, Jerry Li, and Aleksander Madry · 2018
Cited alongside, same era.
Analyzing federated learning through an adversarial lens
Arjun Nitin Bhagoji, Supriyo Chakraborty, Prateek Mittal, and Seraphin Calo · 2019
Cited alongside, same era.
Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification
Patrick Helber, Benjamin Bischke, Andreas Dengel, and Damian Borth · 2019
Cited alongside, same era.
Measuring and analyzing search engine poisoning of linguistic collisions
Matthew Joslin, Neng Li, Shuang Hao, Minhui Xue, and Haojin Zhu · 2019
Cited alongside, same era.
Attacking graph-based classification without changing existing connections
Xuening Xu, Xiaojiang Du, and Qiang Zeng · 2020
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https://github.com/leftthomas/SimCLR, 2021
A PyTorch implementation of SimCLR · 2021
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https://www.kaggle.com/ashishjangra27/face-mask-12k-images-dataset, 2021
Face Mask Detection 12K Images Dataset · 2021
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https://www.kaggle.com/c/tiny-imagenet/overview, 2021
MicroImageNet classification challenge · 2021
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https://github.com/facebookresearch/moco, 2021
The official PyTorch implementation of MoCo · 2021
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Data poisoning attacks to local differential privacy protocols
Xiaoyu Cao, Jinyuan Jia, and Neil Zhenqiang Gong · 2021
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Data poisoning against differentially-private learners: Attacks and defenses
Yuzhe Ma, Xiaojin Zhu, and Justin Hsu · 2019
Cited alongside, same era.
Attacking graph-based classification via manipulating the graph structure
Binghui Wang and Neil Zhenqiang Gong · 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.
A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
Cited alongside, same era.
Local model poisoning attacks to byzantine-robust federated learning
Minghong Fang, Xiaoyu Cao, Jinyuan Jia, and Neil Gong · 2020
Cited alongside, same era.
Influence function based data poisoning attacks to top-n recommender systems
Minghong Fang, Neil Zhenqiang Gong, and Jia Liu · 2020
Cited alongside, same era.
Witches’ brew: Industrial scale data poisoning via gradient matching
Jonas Geiping, Liam H Fowl, W Ronny Huang, Wojciech Czaja, Gavin Taylor, Michael Moeller, and Tom Goldstein · 2020
Cited alongside, same era.
Poisoning the unlabeled dataset of semi-supervised learning
Nicholas Carlini · 2021
Later among the works it cites.
De-pois: An attack-agnostic defense against data poisoning attacks
Jian Chen, Xuxin Zhang, Rui Zhang, Chen Wang, and Ling Liu · 2021
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Data poisoning attacks and defenses to crowdsourcing systems
Minghong Fang, Minghao Sun, Qi Li, Neil Zhenqiang Gong, Jin Tian, and Jia Liu · 2021
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Data poisoning attacks to deep learning based recommender systems
Hai Huang, Jiaming Mu, Neil Zhenqiang Gong, Qi Li, Bin Liu, and Mingwei Xu · 2021
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Subpopulation data poisoning attacks
Matthew Jagielski, Giorgio Severi, Niklas Pousette Harger, and Alina Oprea · 2021
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Intrinsic certified robustness of bagging against data poisoning attacks
Jinyuan Jia, Xiaoyu Cao, and Neil Zhenqiang Gong · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Certified robustness of graph neural networks against adversarial structural perturbation
Binghui Wang, Jinyuan Jia, Xiaoyu Cao, and Neil Zhenqiang Gong · 2021
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MPAF: Model poisoning attacks to federated learning based on fake clients
Xiaoyu Cao and Neil Zhenqiang Gong · 2022
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Poisoning and backdooring contrastive learning
Nicholas Carlini and Andreas Terzis · 2022
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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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BadEncoder: Backdoor attacks to pre-trained encoders in self-supervised learning
Jinyuan Jia, Yupei Liu, and Neil Zhenqiang Gong · 2022
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Poisoning attacks to local differential privacy protocols for key-value data
Yongji Wu, Xiaoyu Cao, Jinyuan Jia, and Neil Zhenqiang Gong · 2022
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